WSEAS Transactions on
Print ISSN: 1790-5052
Volume 10, 2014
Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.
Volume 10, 2014
Title of the Paper: Towards Enhancing the Face Detectors Based on Measuring the Effectiveness of Haar Features and Threshold Methods
Authors: Nidal F. Shilbayeh, Khadija M. Al-Noori, Asim Alshiekh
Abstract: Face detection has been regarded as the most complex and challenging problem in the field of computer vision, due to the large intra-class variations caused by the changes in facial appearance, lighting, and expression. Face detection is the essential first step towards many advanced computer vision, biometrics recognition and multimedia applications, such as face tracking, face recognition, and video surveillance. One of the most famous approaches that is successful is the Viola & Jones algorithm. In this paper, systems were designed based on this approach to measure the effectiveness of the different Haar feature types, and to compare two types of threshold computing methods. The two methods used for computing thresholds are the average of means and the optimal threshold methods. There are 8 different Haar features has been used in building these systems. The implemented systems have been trained using a handpicked database. The database contains 350 face and nonface images. Adaboost algorithm has been used to build our detectors. Each detector consists of 3 cascade stages. In each stage, we randomly use a number of weak classifiers to build the strong classifier. Each weak classifier is computed based on threshold before entering the Adaboost algorithm. If the image can pass through all stages of the detector, then the face will be detected. The detectors have been tested using the CMU+MIT database. Some recommendations have been suggested according to the Haar features and the computed threshold to improve the face detection of Viola Jones approach.
Keywords: Face Detection, Haar-Like Features, Pattern Recognition, Weak Classifier, Integral Image, Strong Classifier, Adaboost Algorithm.
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #68, pp. 662-673
Title of the Paper: Multiobjective Image Data Hiding Based on Neural Networks and Memetic Optimization
Authors: Hieu V. Dang, Witold Kinsner, Yingxu Wang
Abstract: This paper presents a hybridization of neural networks and multiobjective memetic optimization for an adaptive, robust, and perceptual data hiding method for colour images. The multiobjective optimization problem of a robust and perceptual image data hiding is introduced. In particular, trade-off factors in designing an optimal image data hiding to maximize the quality of watermarked images and the robusteness of watermark are investigated. With the fixed size of a logo watermark, there is a conflict between these two objectives, thus a multiobjective optimization problem is introduced. We propose to use a hybrid between general regression neural networks (GRNN) and multiobjective memetic algorithms (MOMA) to solve this challenging problem. Specifically, a GRNN is used for the efficient watermark embedding and extraction in the wavelet domain. Optimal watermark embedding factors and the smooth parameter of GRNN are searched by a MOMA. The experimental results show that the propsed approach achieves adaptation, robustness, and imperceptibility in image data hiding.
Keywords: Information hiding; image data hiding; image watermarking; multiobjective optimization; memetic optimization; general regression neural networks; wavelet transforms; human visual system; quality metrics
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #67, pp. 645-661
Title of the Paper: Noise Canceller Using a New Modified Adaptive Step Size LMS Algorithm
Authors: Thamer M. Jamel, Haiyder A. Mohamed
Abstract: In this paper, the performance of adaptive noise canceller (ANC) in stationary environment is improved by using a new proposed variable step size LMS algorithm. The algorithm is called (Absolute Average Error- Based Adjusted step size LMS algorithm (AAE-ASSLMS)). The adjusted step size is based on the absolute average value of the current and the previous sample errors. The algorithm has low level steadystate misadjustment compared with the standard LMS and another Variable Step Size LMS (VSSLMS) algorithm for ANC. The proposed algorithm achieved (16, 13) dB difference of attenuation factor in a steady state compared with the LMS and VSSLMS algorithms respectively. Moreover, the proposed algorithm is insensitive to the both power variation of reference input and different signal to noise ratios at the primary input of ANC.
Keywords: Adaptive noise canceller, LMS algorithm, Variable step size
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #66, pp. 637-644
Title of the Paper: An Adaptively Iterative Method of Document Image Binarization
Authors: Ning Liu, Guanxiang Wang, Caiping Lv, Yu Wang
Abstract: Document image binarization is difficult when the image is affected by background noise or non- uniformly illuminated. In this paper, an adaptively method is proposed to address the above problems and thus get expected binarization results. This method begins by defining a filter window length with initialized stroke width, and then transforms the document image into a feature space with Gaussian kerneled Bhattacharyya distance and sets up a threshold with Ostu’s method to temporarily binarize the image, and in the end, it uses the stroke width extracted from the newly obtained image to update the filter window length until the iteration convergent. The proposed method has been tested on the DIBCO(2009-2012) databases and get acceptable results on most images in these databases. In addition, expected results have been achieved when we tested this method on several other seriously noised and shadowed document images, even with various resolutions, which indicates our method is effective.
Keywords: Αdaptive binarization, document image, Bhattacharyya distance, stroke width, run-length histogram
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #65, pp. 627-636
Title of the Paper: Design of Stable IIR Filters with Prescribed Flatness and Approximately Linear Phase
Authors: Yasunori Sugita
Abstract: This paper presents a design method of infinite impulse response (IIR) filters with prescribed flatness and approximately linear phase characteristics using quadratic programming (QP). It is utilized in this paper for the design of Chebyshev type, inverse Chebyshev type filters, and simultaneous Chebyshev type filters with the prescribed flatness in passband and stopband. In the proposed method, the flatness condition in stopband is preincorporated into the transfer function. Then, the flatness condition in passband and the filter’s stability condition are, respectively, added to the QP problem as the linear matrix equality and linear matrix inequality constraints. As a result, the proposed method can easy design these three types of filter by only change of the design parameters. The effectiveness of the proposed design method is illustrated with some examples.
Keywords: IIR filter, Flat magnitude, Flat group delay, Equiripple characteristics, Quadratic programming
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #64, pp. 619-626
Title of the Paper: Motion Estimation Algorithm for HEVC Suitable for Hardware Implementation
Authors: Shikai Zuo, Mingjiang Wang, Liyi Xiao
Abstract: HEVC being developed in the video coding standard(The video coding standard of HEVC being developped ) is a new generation of video coding standards for HD resolution video encoding. It is difficult to implement HEVC real time coding in current hardware for the algorithm’s complextivity, so the algorithm optimization and hardware acceleration of HEVC become research hot spots. The motion estimation unit of HEVC occupy more than 50% of the computation time in the ITU-T standard coding software, so the algorithm optimization can reduce the encoding time largely. Therefore，this paper proposes a new parallel processing method that the LCU and the PU block are divided for computing motion estimation parameters at the same time. The test results shows that, PSNR is decreased 0.005db and compression rate is decreased 0.026 percentage , the algorithm can increase the processing speed of motion estimation by 77.2%, compare with full search algorithm. The paper algorithm is suitable for hardware implementation, for the parameters of various motion estimation block in the same LCU can be computed parallelly and memery access is regular.
Keywords: Video Coding, HEVC/H.264 encoder, Fast Motion Estimation, 1080P, Parallel Computing
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #63, pp. 611-618
Title of the Paper: Texture: A Granular Synthesizer for Real-Time Sound Generation
Authors: Giorgio Nottoli, Giovanni Costantini, Andrea Angelini, Massimiliano Todisco, Daniele Casali
Abstract: Sound synthesis is a subject where last development of electronics had made a significant boost. Since it’s beginning, it developed on two main branches: on one side it tried to imitate other instruments, trying to re-create sounds that already exist. On the other side, it followed an aim that we can consider someway opposite: producing new sounds, exploring new possibilities, and allowing composers to follow new paradigms in musical composition. Imitating other instruments can be useful for various reasons: the electronic version of an instrument has often very lower cost with respect to the original one, and also lower weight. Besides, it can have some advantages, as the capability to be played by a computer or to use headphones. Producing new sounds, on the other hand, means often better fitting than any acoustic instrument with the idea of a musician. The issue, in this case, is to give the musician the opportunity to easily control all necessary parameters, in order to obtain the desired result. So, while on the first branch we can easily say that the better instruments are the ones that imitate more closely real instruments, on the second branch the variety of produced timbres is important, but it is almost useless if it is not accompanied by a tool to control a huge set of parameters in an efficient way. In this paper, we focused on the production of new sounds, and we present a system called Texture, that generate sounds in real-time. The current version of Texture is available both on Windows and on OSX operating systems, both as a Virtual Studio Technology (VST) and as Audio Units (AU). The system is based on the Granular Synthesis, which is a method that produces complex sounds by mixing together simple elements called “grains”, but it extend the classical method with some new features that bring more richness and variety to the sound. The software comes with a graphical interface and applications that allow to control the synthesis parameters in an effective way, and that give the musician the opportunity to add expression to the sound. This goal is reached by means of neural networks.
Keywords: Real-time systems, sound synthesis, granular synthesis, audio plugins, VST, AU
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #62, pp. 601-610
Title of the Paper: A Minimum Distance-Based Method for the Classification Problem
Authors: Jianqiang Gao, Lizhong Xu
Abstract: In this paper, a kernel fuzzy discriminant analysis minimum distance-based approach for the classifi- cation of face images is proposed to deal with face classification problem (we call this method mdkfda/qr as an abbreviation). A superiority of the mdkfda/qr is its computational efficiency and can avoid the singularity. In the proposed method, the membership degree is incorporated into the definition of between-class and within-class scatter matrixes to get fuzzy between-class and within-class scatter matrixes. The mdkfda/qr approach was com- pared with kernel discriminant analysis (KDA) and fuzzy discriminant analysis (FDA) two algorithms in terms of classification accuracy. Experiments on ORL and FERET two real face datasets are performed to test and evaluate the effectiveness of the proposed algorithm on classification accuracy. The results show that the effect of mdkfda/qr method can achieve higher classification accuracy than KDA and FDA methods.
Keywords: Kernel discriminant analysis, Fuzzy membership, QR decomposition, Classification, mdkfda/qr
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #61, pp. 592-600
Title of the Paper: An Open GIS for the Significance Analysis of Displacements Arising from GPS Networks Repeated Over Time: An Application in the Area of Castrovillari
Authors: Vincenzo Barrile, Giuseppe M. Meduri, Giuliana Bilotta
Abstract: As is well known, GIS is a powerful tool to process, analyze and display spatial and temporal data whose standard applications are already tested and widely used in various application areas. At the laboratory of Geomatics, Mediterranean University of Reggio Calabria, we implemented a project for the complete realization of an open GIS for calculating the significance of the shifts resulting from GPS data acquired networks, repeated over time, without a priori information on the stability of the points themselves. The monitoring of geodynamic phenomena is constantly evolving thanks to the use of increasingly refined techniques. The increasing availability of data acquired over time, through the GPS system allows creating specific models able to simulate the situation in question. The main objective of this contribute is to provide the results from a long series of GPS data acquired over time on a network straddling an active fault, for the estimation of surface deformation in Castrovillari. The geodetic observations based on GPS can also provide useful information to the refinement of models of geophysical monitoring and prevention of natural disasters in areas of high seismic risk in presence of active faults.
Keywords: Key-Words: Geophysical monitoring, GPS, Geodynamic phenomena, Surface deformations, Geodetic observations
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #60, pp. 582-591
Title of the Paper: Speech Enhancement based on Fractional Fourier Transform
Authors: Jingfang Wang
Abstract: As many traditional de-noising methods fail in the intensive noises environment and are unadaptable in various noisy environments, a method of speech enhancement has been advanced based on dynamic Fractional Fourier Transform （FRFT）filtering. The acoustic signals are framed. The renewing methods are put in FRFT optimal disperse degree of noising speech and this method is implemented in detail. By TIMIT criterion voice and Noisex-92, the experimental results show that this algorithm can filter noise from voice availably and improve the performance of automatic speech recognition system significantly. It is proved to be robust under various noisy environments and Signal-to-Noise Ratio (SNR) conditions. This algorithm is of low computational complexity and briefness in realization.
Keywords: Acoustic signal, Fractional Fourier Transform(FRFT), Speech Enhancemen, de-noising, auto-adaptive processing, Dynamic filtering
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #59, pp. 576-581
Title of the Paper: Parametric Rao Test for Multichannel Adaptive Generalized Detector
Authors: Vyacheslav Tuzlukov
Abstract: The parametric Rao test for multichannel signal detection by the adaptive generalized detector (GD) constructed based on the generalized approach to signal processing in noise is derived by modeling the disturbance signal as a multichannel autoregressive process. The parametric Rao test takes a form identical to that of parametric GD for space-time adaptive processing in airborne surveillance radar systems and other similar applications. The equivalence offers new in-sights into the performance and implementation of the GD. Specifically, the Rao/GD is an asymptotically (in the case of large samples) parametric generalized likelihood ratio test generalized detector (GLRT GD) due to an asymptotic equivalence between the Rao test and the GLRT/ GD. The asymptotic distribution of the Rao/GD test statistic is obtained in the closed form, which follows an exponential distribution under the null hypothesis (the target return signal is absent) and, respectively, a non-central Chi-squared distribution with two degrees of freedom under the alternative hypothesis (the target return signal is present). The noncentrality parameter of noncentral Chi-squared distribution is determined by the output signal- to-interference-plus-noise ratio of a temporal whitening filter. Since the asymptotic distribution at the null hypothesis is independent of the unknown parameters, the Rao/GD asymptotically achieves constant false alarm rate (CFAR) GD. Numerical results show that these results are superior in predicting the performance of the parametric adaptive matched filter even with moderate data support.
Keywords: Generalized detector, space-time adaptive processing, multichannel generalized detector, adaptive matched filter, adaptive coherence estimator detector, clutter, jamming
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #58, pp. 561-575
Title of the Paper: On the Linear Relation of Signals
Authors: Edi Cahyono
Abstract: In this paper two signals over finite and closed interval of time are considered. A linear relation of the two with shifting is defined. In general, when a signal is expressed linearly of another with shifting, this gives an error. The absolute error should be minimized to have the best approximation. For the case of discrete signals without shifting, minimizing this error is just the well-known least square method. Hence, the proposed relation of signals is a generalization of the least square method. Criterion of approximating a signal linearly of the other is based on the relative error. The relative error is defined by comparing the norm of absolute error with the norm of the normalized approximated signal. Geometric interpretation and the applications in finance are also discussed. Especially in finance, the relation of signals can be applied to predict the dynamics of stocks, exchange rates and commodity prices. Predicting such dynamics on itself is very difficult, especially for high frequency data.
Keywords: Relation of signals, Norm, Relative error, Dynamics of stocks, exchange rates, Commodity prices
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #57, pp. 555-560
Title of the Paper: New Multipurpose Oriented Stereo Image Watermarking Algorithm for 3D Multimedia
Authors: Wujie Zhou, Ting Luo, Zhongpeng Wang, Mingkun Feng, Jianfeng Weng, Xin Li
Abstract: Most of digital watermarking algorithms have been designed for only single purpose. In this paper, a new multipurpose oriented stereo image watermarking algorithm is proposed for three dimensional multimedia, which can be used for copyright protection, content authentication and tamper detection in three dimensional (3D) multimedia. Specifically, host stereo image is divided into non-overlapping blocks, and the chaotic feature watermarks are generated according to the stability of low frequency coefficients and largest singular value. As there are redundancies between the left and right views of stereo image, each block of the two views is classified into matchable or non-matchable block to embed digital watermarks with different purposes. At the receiving side, using stereo marching technique as a bridge, the robust and fragile watermarks can be blindly extracted without access to the host stereo image. Meanwhile, the robustness of stereo image watermarking is improved, and a hierarchical tamper detection scheme is presented to ensure the accuracy of tamper localization. Especially, Level-2 detection is employed to improve previously obtained detection results to enhance authentication accuracy. Experimental results show that the proposed algorithm is quite robust to attacks, such as noise, filtering, JPEG compression, cropping and size scaling. Moreover, the experimental results also show that the proposed algorithm can detect tamper accurately and locate forgery effectively.
Keywords: Stereo image watermarking, copyright protection, authentication, multipurpose, matchable block and non-matchable block, chaotic feature watermark
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #56, pp. 544-554
Title of the Paper: On the Designing of Fractional Order FIR Differentiator Using Radial Basis Function and Window
Authors: Manjeet Kumar, Tarun Kumar Rawat
Abstract: The previous work in , Tseng et al. have designed a fractional order differentiator using radial basis function by directly truncating the coefficients to approximate the fractional order derivativeD® of the given digital signal. This paper presents the designing of fractional order differentiator using radial basis function and window. Three design examples are given to illustrate that the use of window along with radial basis function method, improve the frequency response characteristics and minimize the integral root square error than the existing radial basis function method.
Keywords: Fractional order derivative, Digital differentiator, Grunwald-Letnikov derivative, Radial basis function (RBF)
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #55, pp. 538-543
Title of the Paper: Multimodal Emotion Recognition Integrating Affective Speech with Facial Expression
Authors: Shiqing Zhang, Xiaohu Wang, Gang Zhang, Xiaoming Zhao
Abstract: In recent years, emotion recognition has attracted extensive interest in signal processing, artificial intelligence and pattern recognition due to its potential applications to human-computer-interaction (HCI). Most previously published works in the field of emotion recognition devote to performing emotion recognition by using either affective speech or facial expression. However, Affective speech and facial expression are mainly two important ways of human emotion expression, as they are the most natural and efficient manners for human beings to communicate their emotions and intentions. In this paper, we aim to develop a multimodal emotion recognition system integrating affective speech with facial expression and investigate the performance of multimodal emotion recognition at the feature-level and at the decision-level. After extracting acoustic features and facial features related to human emotion expression, the popular support vector machines (SVM) classifier is employed to perform emotion classification. Experimental results on the benchmarking eNTERFACE’05 emotional database indicate that the given approach of multimodal emotion recognition integrating affective speech with facial expression obtains obviously superior performance to the single emotion recognition approach, i.e., speech emotion recognition or facial expression recognition. The best performance obtained by using the product rule at the decision-level fusion is up to 67.44%.
Keywords: Mutimodal emotion recognition, affective speech, facial expression, support vector machines, speech emotion recognition, facial expression recognition
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #54, pp. 526-537
Title of the Paper: An Effective Recurrence Formula for Calculating Lower Cramer-Rao Bounds in Case the State-Vector is Constant
Authors: Dmitriy G. Arsenjev, N. A. Berkovskii
Abstract: An effective method for calculating the Bayesian lower unconditional Cramer-Rao bound on condition that the state-vector is constant has been proposed. The recurrence formula for calculating the Fisher information matrix is proved. The method is applicable to arbitrary model noises including non-Gaussian ones. The effectiveness of the approach proposed is shown by applying to the bearing-only tracking problem.
Keywords: Cramer-Rao bound, Bayesian inference, Bearing-only tracking, unconditional covariance matrix, Fisher matrix
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #53, pp. 520-525
Title of the Paper: A Survey on Remote Sensing Scene Classification Algorithms
Authors: Debabrata Ghosh, Naima Kaabouch
Abstract: Scene classification has been widely utilized in various remote sensing applications. Successful image classification depends on several factors, such as availability of data, complexity of available data, availability of ancillary data, expertise of an analyst, availability of suitable classification algorithms, etc. There is no single best classification method that would be suitable for all applications. This paper aims at highlighting the present-day practices of scene classification by summarizing the major scene classification categories available in the literature. Research shows that high-level classification outperforms the other classification methods for almost any kind of data, however, at the cost of high computation. Further research is needed to improve classification accuracy and at the same time reduce computational complexity in order to make a classification method more suitable for real time applications.
Keywords: Nearest Neighbor, Support Vector Machine, Artificial Neural Network, Decision Tree
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #52, pp. 504-519
Title of the Paper: Comparison between Two Methods for Monitoring Deformation with Laser Scanner
Authors: Vincenzo Barrile, Giuseppe M. Meduri, Giuliana Bilotta
Abstract: This contribute describes two methods for monitoring and control of mountain areas with Terrestrial Laser Scanner using laser scans performed in two time periods, and having as aim the study of possible deformations. In the first method, the registration of scans at each epoch was made using the algorithm ICP (Iterative Closest Point) while the generation of the DEM for analysis of the ΔDEM differences between the two epochs was made with the RANSAC (RANdom SAmple Consensus) algorithm. With the second method, the registration of the point cloud for each period and then the estimation of displacement took place with a procedure based on the algorithm “Least squares 3D surface matching” without the need to use the target scans and DEM generation.
Keywords: Laser Scanner - ICP algorithm – DEM - RANSAC algorithm - Least squares 3D surface matching
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #51, pp. 497-503
Title of the Paper: Combining Spectral and Fractal Features for Emotion Recognition on Electroencephalographic Signals
Authors: Camilo E. Valderrama, Gonzalo Ulloa
Abstract: Recent studies have attempted to recognize emotions by extracting spectral and fractal features from electroencephalographic signals; however, up to now none of them have combined these two features to recognize emotions. This paper aims at providing a comparison between an accuracy rate of an approach that recognizes emotions by extracting both spectral and fractal features with that of those that extract only one of these features. To this end, we designed and implemented a procedure that recognizes positive and negative emotions by extracting spectral, fractal, or both features. Next, using this procedure, we built three different approaches to recognize positive and negative emotions; the first one extracted both spectral and fractal features, whereas the other two extracted each type of feature separately. Then, the accuracy rate of the approaches was calculated and compared among them. The comparison showed that the spectral-fractal approach recognizes emotions more accurately than the spectral and fractal approaches in 96% and 79% of the time, respectively. This suggests that it is possible to develop a more effective emotion recognition method by extracting both spectral and fractal features than extracting only one type of them.
Keywords: Affective Computing; Discrete Wavelet Transform; Electroencephalogram; Emotion recognition; Multifractal Analysis; Support Vector Machine; Pattern recognition
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #50, pp. 481-496
Title of the Paper: Experimentations and Integrated Applications Laser Scanner/GPS for Automated Surveys
Authors: Vincenzo Barrile, Giuseppe M. Meduri, Giuliana Bilotta
Abstract: This contribution is based on studies aimed to a “quick” resolution of an integrated problem about self-localizing and perimetering through mobile devices. We applied the adopted methodology, derived from research and applications, on a real case study (outdoors) by using the following surveying tools: a kinematic Global Positioning System (GPS) and a Laser Scanner supporting a “mobile platform” (deployed on a mobile platform). A “GS14” GPS receiver provided by Leica Geosystem and a two-dimensional Laser Scanner provided by the Automation and Control Laboratory of the University “Mediteranea” of Reggio Calabria were positioned on an experimental mobile system specifically designed to simulate the behaviour of a future fully automated platform. This study focuses on the experimental development of a “quick” methodology for the traditional land surveying through a Laser Scanner alongside with GPS receivers in a three dimensional centimetric resolution within a single system of reference made up of individual scans operated by a “Stop-and-Go” device.
Keywords: GPS, Laser scanner 3D, Self-localization, Survey
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #49, pp. 471-480
Title of the Paper: 3D Visualization of Radar Coverage Considering Electromagnetic Interference
Authors: Hang Qiu, Lei-Ting Chen, Guo-Ping Qiu, Chuan Zhou
Abstract: Radar plays an important role in many domains, such as target searching, target tracking and dynamic objects detection. However, the electromagnetic information of radar is invisible and full of changes in real time, which restricts users to plan and design the radar systems. In recent years, with the development of interactive visualization technology, 3D visualization of the abstract information of radar coverage under the influence of complicated environment becomes a hotspot. In this paper, we present a method to represent radar coverage considering the electromagnetic interference. Based on the radar equation, from the perspectives of pitch and azimuth angles to achieve 3D modeling of radar coverage through discrete subdivision, and the radar model possesses self-adaptability to different levels of detail. The 3D radar detection range under the influence of electromagnetic interference is analyzed and addressed based on radar jamming model. Experiments demonstrate that our method not only can efficiently complete the three-dimensional modeling of radar, but also visually show the true radar coverage under the influence of complex electromagnetic environment.
Keywords: 3D visualization, radar coverage, levels of detail (LOD), electromagnetic interference, nonuniform sampling
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #48, pp. 460-470
Title of the Paper: Diversity Detection in Non-Gaussian Noise over Fading Channels by Generalized Detector
Authors: Vycheslav Tuzlukov
Abstract: In this paper, we consider the problem of M-ary signal detection based on the generalized approach to signal processing (GASP) in noise over a single-input multiple-output (SIMO) channel affected by the frequ-ency-dispersive Rayleigh distributed fading and corrupted by the additive non-Gaussian noise modelled as spherically invariant random process. We derive both the optimum generalized detector (GD) structure based on GASP and a suboptimal reduced-complexity GD applying the low energy coherence approach jointly with the GASP in noise. Both GD structures are independent of the actual noise statistics. We also carry out a perfo-rmance analysis of both GDs and compare with the conventional receivers. The performance analysis is carried out with reference to the case that the channel is affected by a frequency-selective fading and for a binary freq-uency-shift keying (BFSK) signalling format. The results obtained through both a Chernoff-bounding technique and Monte Carlo simulations reveal that the adoption of diversity also represents a suitable means to restore pe-rformance in the presence of dispersive fading and impulsive non-Gaussian noise. It is also shown that the sub-optimal GD incurs a limited loss with respect to the optimum GD and this loss is less in comparison with the conventional receiver.
Keywords: Generalized detector (GD), additive non-Gaussian noise, array processing, diversity, detection performance, generalized approach to signal processing (GASP), spherically invariant random processes
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #47, pp. 444-459
Title of the Paper: Text/ Background Separation in the Degraded Document Images by Combining Several Thresholding Techniques
Authors: Abderrahmane Kefali, Toufik Sari, Halima Bahi
Abstract: Extract the text from the background is an important step in all process of document analysis and recognition. If this extraction is easy for document images of good quality by applying simple techniques of global thresholding, the images of degraded documents require a more accurate analysis and we have recourse in this case to local methods. Indeed, these latter are generally more efficient and provide better results than the global methods but they are very slow because of the threshold calculation which is performed separately for each pixel based on the information of its neighborhood. In this article, we try to solve this problem by proposing a hybrid thresholding technique which combines the advantages of the two families of methods, speed and performance. The idea is to precede a thresholding in two passes: globally in order to class the most of pixels and then locally on the remaining pixels. The approach has been tested on a standard collection and compared with well known methods, and the results are encouraging.
Keywords: Binarization, Degraded Documents, Document Preprocessing, Combination of Thresholding Methods, Evaluation of Binarization Methods, Hybrid Thresholding
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #46, pp. 436-443
Title of the Paper: An Image Saliency Detection Method by Constructing Graph Model
Authors: Zhenghao Hu, Qiuping Jiang, Zhutuan Li, Feng Shao
Abstract: In this paper, we present an image saliency detection method by constructing graph model. We extract color, texture and compactness features and segment superpixels from an input image to construct a graph model. Then, saliency for each is measured by calculating random walker probability on the node. Extensive results on MSRA dataset containing 1000 test images with ground truths demonstrate that the proposed saliency model outperforms the state-of-the-art saliency models with higher precision and recall performances.
Keywords: Saliency detection, graph model, superpixel segmentation, random walk
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #45, pp. 429-435
Title of the Paper: Novel Fractal-Wavelet Technique for Denoising Side-Scan Sonar Images
Authors: Fu-Tai Wang, C.-Y. Jenny Lee, Hsiao-Wen Tin, Shao-Wei Leu, Chan-Chuan Wen, Shun-Hsyung Chang
Abstract: Side-scan signals collected from the seabed are constructed based on elements of bottom roughness, which vary in texture and in the time they are collected. Image denoising, A procedure used for extracting image texture information and removing or reducing as much noise as possible, is a difficult problem. This study proposes a denoising algorithm based on an elaborative approach for measuring image roughness as an alternative to the fractal-wavelet (FW) coding process. By using this approach, texture similarity can be effectively captured. Because roughness is a property used to qualify image texture and a fractal dimension (FD) can be used to indicate the degree of complexity of image roughness, this study proposed an approach, namely the roughness entropy FD (REFD) method, for measuring the distribution of roughness in an image. This study applied the REFD algorithm to the FW coding process as the REFD FW algorithm. The proposed denoising algorithm approximates the parts of a noise-free image by determining the similarity distance between the two REFD values of domain-range subtrees, discarding as much noise as possible. The minimal similarity distance is used to quantify the degree of texture similarity between domain-range subtrees. This study conducted experiments on three side-scan sonar images of an undersea pipeline that were captured in Taiwan using a Polaris camera in various configurations in order to investigate the corresponding quality of the images by using two error criteria: mean square error and the peak signal-to-noise ratio. The experimental results indicated that the REFD is useful for range-domain matching in an FW coder to approximate the experimental images effectively. The proposed REFD FW algorithm is adaptable in denoising side-scan sonar images, and the images are more visually appealing.
Keywords: Fractal dimension, fractal-wavelet denoising, image denoising, image roughness, self-similarity, side-scan sonar images
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #44, pp. 418-428
Title of the Paper: FPGA Dedicated Hardware Architecture of 3D Medical Image Reconstruction: Marching Cubes Algorithm
Authors: Bouraoui Mahmoud, Nadia Nacer, Manel Mili, Mohamed Hedi Bedoui
Abstract: Generally, the implementation of various treatments of medical images, especially the 3D reconstruction, should support a real-time execution of the algorithm on the architecture: It is to meet the constraints of latency and circuit space while minimizing the resource consumption. We are interested in this project for a 3D reconstruction of medical images on a platform based on an FPGA. We have as an objective the specification and hardware implementation of the reconstruction algorithm, the Marching Cubes.
Keywords: FPGA, Implementation, 3D, 2D Images, Reconstruction, Marching Cubes, Medical image
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #43, pp. 411-417
Title of the Paper: An Algorithm of Camera Sabotage Detection Using Contourlet
Authors: Shuang Liang, Ting Li, Wei Guo, Yu Wang
Abstract: Contourlet is one of the new topics in image processing and video processing. Besides a lot of theoretical works about contourlet transform, its applications have roused enough interest as a critical means of multi-scale geometric analysis. This article, focusing on camera sabotage detection, extends the application of contourlet trans- form to video processing. A new algorithm to detect camera sabotage based on contourlet transform is proposed and experiment results show that the proposed algorithm is powerful and more efficient. Moreover, a comparison of results obtained by this algorithm and the one based on the 9-7 wavelet is made.
Keywords: Camera sabotage detection, Contourlet transform, Filter design, McClellan transform
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #42, pp. 404-410
Title of the Paper: Low-Complexity Image Denoising via Analytical Form of Generalized Gaussian Random Vectors in AWGN
Authors: Pichid Kittisuwan
Abstract: The application of the wavelet transform in image denoising has shown remarkable success over the last decade. In this paper, we present new Bayesian estimators for spherically-contoured generalized Gaussian (GG) random vectors in additive white Gaussian noise (AWGN). The derivations are an extension of existing results for Pearson type VII random vectors. In fact, Pearson type VII distribution have higher-order moment in statistical parameter for fitted the data such as mean, variance, and kurtosis. Indeed, where high-order statistics were used, better performance can be obtained but with much higher computational complexity. In Specific case, GG random vectors is similar to Pearson Type VII random vectors. However, the specific case of GG random vectors have only first few statistical moments such as variance. So, the proposed method can be calculated very fast, with out any contours. In our experiments, our proposed method gives promising denoising results with moderate complexity.
Keywords: Bayesian Estimation, Spherically-Contoured Generalized Gaussian (GG) Random Vectors, Wavelet Denoising
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #41, pp. 398-403
Title of the Paper: A New Method Judging the Interpolation Direction
Authors: Congyan Chen, Zhiyuan Chen, Shi Qiu
Abstract: The discrete Fourier transform (DFT) algorithms are commonly used in frequency estimation. The interpolation direction of the interpolated algorithms based on DFT is always defined by the information of spectral amplitude, such as the Rife algorithm. In the case of low signal to noise ratio (SNR), false decision of the interpolation direction occurs sometimes. However, decreasing false rate of the interpolation direction decision can improve the frequency estimation accuracy directly. In this paper, a new method to judge the interpolation direction based on spectral phase information instead of amplitude is presented, which is helpful to improve the original Rife algorithm or other interpolated algorithms based on DFT. The simulation results demonstrate that the false rate of interpolation direction judged by the proposed method is obviously lower than that by the original Rife algorithm in the case of low SNR, and also show that its achievement of a low variance close to the Cramer-Rao lower bound.
Keywords: Frequency estimation; Rife algorithm; interpolation direction
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #40, pp. 392-397
Title of the Paper: XZ-Shape Histogram for Human-Object Interaction Activity Recognition based on Kinect-like Depth Image
Authors: M. A. As’Ari, U. U. Sheikh, E. Supriyanto
Abstract: This paper introduces XZ-shape histogram in recognizing human performing activities of daily living (ADLs) which focuses on human-object interaction activities based on Kinect-like depth image. The evaluation framework was formulated in order to compare XZ-descriptor with previous shape histogram as well as X-shape histogram and Z-shape histogram. Each descriptor was segmented into several cases according to number of shells and symbols used in vector quantization process which was executed using our own dataset called RGBD-HOI. This study showed that XZ-shape histogram managed to outperform the other 3D shape descriptors along with the excellent one that compares the performance inferred by the area under receiver operating characteristic curve (AUC-ROC).The results of this study not only demonstrate the implementation of 3D shape descriptor in the dynamic of human activity recognition but also challenge the previous shape histograms in terms of providing low dimension descriptor that capable in improving the discrimination power of human-object interaction activity recognition.
Keywords: Human-object interaction, activities of daily living (ADLs), RGBD image, shape histogram Kinect-like depth image
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #39, pp. 382-391
Title of the Paper: A Sparse Signal Reconstruction Perspective for Direction-of-Arrival Estimation with Minimum Redundancy Linear Array
Authors: Xiaoli Ren, Ji Wang, Shuangyin Liu
Abstract: In this paper, a new direction of arrival (DOA) estimation method based on minimum redundancy linear array (MRLA) from the sparse signal reconstruction perspective is proposed. According to the structure feature of MRLA which is obtaining larger antenna aperture through a smaller number of array sensors, MRLA is combined with method to estimate signal DOAs. Simulations demonstrate that the proposed method is effective and compared with method it could estimate more DOAs of signal source, and it is capable of estimating more DOAs with fewer antenna elements.
Keywords: Direction of arrival, minimum redundancy linear array, -singular value decomposition, sparse signal reconstruction
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #38, pp. 374-381
Title of the Paper: Low-Complexity Matrix Embedding Using an Efficient Iterative Search Strategy
Authors: Chi-Yuan Lin, Jyun-Jie Wang
Abstract: This study proposes a novel suboptimal embedding algorithm for binary messages based on a low-weight search embedding (LWSE) strategy. The suboptimal LWSE strategy involves using algorithm to perform an embedding procedure by using a parity check matrix. The optimal embedding algorithm, which is based on the maximun likelihood (ML) algorithm, aims to locate the coset leader and minimize embedding distortion. The optimal embedding based on linear codes can achieve high embedding efficiency but incurs high computation. Conversely, the LWSE does not need to locate the coset leader, but instead requires suboptimal object. Because its corresponding weight remains close to that of the coset leader, the algorithm proceeds in an efficiently iterative manner. When using the optimal ML algorithm for a situation involving the highest operation complexity, the operation complexity of the suboptimal LWSE is linearly proportional to the number of code dimension.
Keywords: Suboptimal embedding algorithm, data hiding, digital watermarking, informed coding, informed embedding, maximun likelihood algorithm
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #37, pp. 363-373
Title of the Paper: Monogenic Signal Theory Based Feature Similarity Index for Image Quality Assessment
Authors: Xue-Gang Luo, Hua-Jun Wang
Abstract: Image quality assessment (IQA) aims to establish generic metrics consistently with subjective evaluations using computational models. Recent phase congruency, which is a dimensionless, normalized feature of a local structure, is used as the structure similarity feature. This paper proposes a novel feature similarity (RMFSIM) index for full reference IQA based on monogenic signal theory. A monogenic phase congruency map, which is equipped to be relatively insensitive to noise variations, is constructed using phase, orientation and energy information of the 2D monogenic signal. The corresponding 1st-order and 2nd-order coefficients of the MPC map are obtained by Riesz transform. The local feature coefficients similarity is computed by the similarity measure and a single similarity score are combined together finally. Experimental results demonstrate that the proposed similarity index is highly consistent with human subjective evaluations and achieves good performance in terms of prediction monotonicity and accuracy.
Keywords: Image quality assessment(IQA); monogenic phase congruency(MPC); human visual system; Feature Similarity Index
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #36, pp. 354-362
Title of the Paper: Cascadable Low Voltage Operated Current-Mode Universal Biquad Filter
Authors: Ravindra Singh Tomar, Sajai Vir Singh, Durg Singh Chauhan
Abstract: A new current-mode universal biquad filter structure using two Z-Copy Current Follower Trans-conductance Amplifiers (ZC-CFTAs), and two grounded capacitors is proposed in this paper. The proposed structure can be configured into either multiple inputs multiple outputs (MIMO) or multiple inputs single output (MISO) configurations. In each configuration, the proposed circuit can realize all the standard filtering responses such as low pass (LP), band pass (BP), high pass (HP), band reject (BR), and all pass (AP), by choosing the current input/output terminals appropriately. The circuit operates at lower supply voltage rails, and for response realization it does not require inverted current input signal(s) and component matching constraints. The proposed circuit offers an advantage of electronic tunability of pole-frequency independent to the quality factor. The effort is further extended to originate an Nth- order LP filter, through direct cascading of proposed circuit blocks. Performances of the proposed circuits were examined through P-SPICE programs on cadence tools using standard CMOS technology.
Keywords: Biquad, CFTA, Current-mode, Universal, Filter
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #35, pp. 345-353
Title of the Paper: Data Processing Method to classify Pc5 ULF Pulsations due to Solar Wind Perturbations at Equatorial Region
Authors: Siti Noor Aisyah Ahmad, Mohamad Huzaimy Jusoh, Khairul Khaizi Mohd Shariff, Mardina Abdullah, Mhd Fairos Asillam, B. Veenadhari, T. Uozumi, S. Abe, A. Yoshikawa, M. G. Cardinal
Abstract: Space weather study has increasingly attracts the attention of many scientists to explore the interaction between solar activity and geomagnetic activity. Observation on Pc5 geomagnetic pulsations with periods ranging from 150-600 seconds due to solar wind perturbations at the equatorial region currently not widely explored. In this paper, we will briefly discuss the data processing methods involve in order to analyze the geomagnetic data observed by magnetometer from geomagnetic observation stations; Tirunelveli (TIR), India, Langkawi (LKW), Malaysia and Yap Island (YAP), Federated States of Micronesia which are located at equatorial region. The explanation of the processing methods is based on the 24-hour data with 1 second sampling interval extracted during quiet and disturbed days. The result indicates that the higher amplitude of H geomagnetic field is recorded during daytime and maintain during nighttime at all analyzed stations. In addition, Pc5 ULF pulsations are corresponding well with the solar wind perturbations.
Keywords: Magnetometer, geomagnetic data, magnetic pulsation, solar wind perturbations and data processing method
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #34, pp. 337-344
Title of the Paper: Power-Efficient Linear Phase FIR Notch Filter Design Using the LARS Scheme
Authors: Wei Xu, Jiaxiang Zhao, Hongjie Wang, Chao Gu
Abstract: In this paper, an effective paradigm based on the Least Angle Regression (LARS) scheme is developed to iteratively compute the power-efficient linear phase FIR notch filters. At each iteration, we compute the equiangular vector and the step size to be taken which are then used to modify our previous prediction of the filter coefficients along the computed equiangular direction. The iteration of the LARS scheme stops when the error defined as the L2-norm of the difference between the computed prediction of the notch filter and the desired notch filter is less than the pre-chosen design error ε . The simulation results demonstrate that the proposed LARS scheme is an effective paradigm to compute power-efficient linear phase notch FIR filters.
Keywords: Least angle regression scheme, notch filter, FIR filter, linear phase, power-efficient,filter design
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #33, pp. 331-336
Title of the Paper: Speaker Verification using Speaker-Specific-Text
Authors: B. Bharathi, T. Nagarajan
Abstract: In speaker recognition tasks, one of the reasons for reduced accuracy is due to closely resembling speakers in the acoustic space. In conventional GMM-based modeling technique, since the model parameters of a class are estimated without considering other classes in the system, features that are common across various classes may also be captured, along with unique features. If the system is designed to use only the unique features of a given speaker with respect to his/her acoustically resembling speaker, then the system is expected to perform better. In this proposed work, the effect of a subset of phonemes, reasonably distinct (unique) to a speaker, in the acoustic sense, on a speaker verification task is investigated. This paper proposes a technique to reduce the confusion errors, by finding speaker-specific phonemes and formulate a text using the subset of phonemes that are unique, for speaker verification task using GMM-based approach and i-vector based approach. We have experimented with three techniques namely, product of likelihood-Gaussians-based distance, Bhattacharyya distance and average loglikelihood- based distance to find out acoustically unique phonemes. Experiments have been conducted on speaker verification task using speech data of 50 speakers collected in a laboratory environment. The experiments show that the Equal Error Rate (EER) has been decreased by 4% and 4.5% using speaker-specific-text when compared to that of GMM and i-vector technique with random-text respectively.
Keywords: Speaker verification, Product of Gaussian, Gaussian Mixture Model, i-vector, acoustic likelihood
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #32, pp. 320-330
Title of the Paper: Novel Detection Algorithm of Speech Activity and the impact of Speech Codecs on Remote Speaker Recognition System
Authors: Riadh Ajgou, Salim Sbaa, Said Ghendir, Ali Chamsa, A. Taleb-Ahmed
Abstract: In this paper, we studied the effects of voice codecs on remote speaker recognition system, considering three types of speech codec: PCM, DPCM and ADPCM conforming to International Telecommunications Union - Telecoms (ITU-T) recommendation used in telephony and VoIP (Voice over Internet Protocol). To improve the performance of speaker recognition in a noisy environment, we propose a new speech activity detection algorithm (SAD) using ''Adaptive Threshold'', which can be simulated with speech wave files of TIMIT (Texas Instruments Massachusetts Institute of Technology) database that allows recognition system to be done under almost ideal conditions. Moreover, the speaker recognition system is based on Vector Quantization as speaker modeling technique and Mel Frequency Cepstral Coefficient (MFCC) as feature extraction technique. Where, the feature extraction proceed after (for testing phase) and before (for training phase) the speech is sending over communication channel. Therefore, the digital channels can introduce several types of degradation. To overcome the channel degradation, a convolutional code is used as error-control coding with AWGN channel. Finely, In our simulation with Matlab we have used 30 speakers of different regions (10 male and 20female), the best overall performance of speech codecs was observed for the PCM code in terms of recognition rate accuracy and runtime.
Keywords: PCM, DPCM, ADPCM, speaker recognition, SAD
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #31, pp. 309-319
Title of the Paper: A Path Loss Calculation Scheme for Highway ETC Charging Signal Propagation
Authors: Chunxiao Li, Dawei He, Zhenghua Zhang, Wanpei Chen, Yuren Du, Xuelong Hu
Abstract: Nowadays, Electronic Toll Collection (ETC) technology is widely used in many countries for highway toll charging. Actually, the ETC charging process can be treated as wireless communication between On Board Unit(OBU: in the vehicle side) and Road Side Unit(RSU: in the ETC exclusive lane side). After the communication link is built between the OBU and RSU, the highway toll gate will be open automatically, and meanwhile, the toll will be charged from drivers’ bank accounts. This process asks for higher accuracy of the propagated signal. For path loss calculation of the charging signal, many previous researches only considered the direct path. However, in our realistic architectures of the highway toll stations, the signal propagation between the OBU and RSU is made up of several paths. Not only the direct path, but also many un-direct paths. Therefore, it is necessary to consider the realistic architectures of the toll stations, and give out a more feasible calculation method. This paper proposed a more feasible path loss calculation scheme for the ETC charging signal, which has considered the reflections impacts from the roof and ground of the station. By simulation, our method indicates that, the reflection effects from the roof and ground cannot be ignored in the realistic charging process. This paper also gives two advices for reducing the reflection impacts: 1) increase the reflection coefficients of roof and ground, which can be used to reduce the path loss brought by reflections; 2)the best suitable distance between the RSU and OBU is about 3m 5m, within this distance, the signal path loss is much lower than other distance ranges.
Keywords: Path Loss, ETC signal, reflection impact, realistic toll station architecture
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #30, pp. 301-308
Title of the Paper: Blind Medical Image Watermarking with LWT – SVD for Telemedicine Applications
Authors: N. Venkatram, L. S. S. Reddy, P. V. V. Kishore
Abstract: This paper highlights the extension of dwt-svd based image watermarking to medical images. In recent times internet has become a primary source of communication between the diagnostics center and the remote doctor located at some hospital. With the use of internet come the problem of data authenticity and the responsibility of the medical practitioner to preserve sensitive information of patients contained in the medical images related to that particular patient. Hence we have made an attempt to solve this problem by using dwt-svd based watermarking technique used for normal images. For medical images quality preservation is obligatory we have used 2D lifting wavelet transform (LWT) instead of dyadic 2D discrete wavelet transform. To test our algorithm we used computer tomography (CT) images as the original images. The watermark is chosen as patient picture which is hidden in a CT medical image while transmitting through internet. The results show that after attacks lwt-svd method gives satisfactory quality both visually and mathematically.
Keywords: Medical Image watermarking, Lifting Wavelet Transform, Singular Value Decomposition, Computer Tomography, lwt-svd watermarking
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #29, pp. 288-300
Title of the Paper: Algorithm of Efficient Computation DSTI-IV Using Cyclic Convolutions
Authors: Ihor Prots’ko, Vasyl Teslyuk
Abstract: The general method for efficient computation of discrete sine transform (DST) of sequences of arbitrary number of points using cyclic convolutions is considered. Forming hashing arrays on the basis of simplified arguments of basis sine transform for synthesis of efficient algorithm is analyzed. The hashing arrays in algorithm define partitioning of the basis into shift cyclic submatrices. The examples for size 8 of four types of DST I-IV using proposed method are analyzed. The hashing arrays, used in the algorithms of synthesis technique, are more versatile and generally better in terms of indexing mapping in comparison with the existing algorithms.
Keywords: Discrete sine transform, types of DST, algorithm, hashing array, synthesis, cyclic convolution
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #28, pp.277-287
Title of the Paper: Algorithm for Signal Parameters Estimation based on the Differential Samples
Authors: Predrag B. Petrović
Abstract: This paper is concerned with the estimation of amplitude and phase of an analog multi-harmonic signal based on a series of differential values of the signal. To this end, assuming the signal fundamental frequency is known before hand (i.e., estimated in an independent stage), a complexity-reduced scheme is proposed here. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The propose algorithm for the calculation of the unknown parameters requires O((2M)2) flops, while the straightforward solution of the obtained equations takes O((2M)3) flops, where M is number of harmonic coefficients. It is proved that the estimation performance of the proposed algorithm can attain Cramer-Rao lower bound (CRLB) for sufficiently high signal-to-noise ratios. It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Keywords: Band-limited signals, differential values, analytical solutions, signal reconstruction, simulation
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #27, pp.263-276
Title of the Paper: Multiple Fault Detection in Typical Automobile Engines: A Soft Computing Approach
Authors: S. N. Dandare, S. V. Dudul
Abstract: Fault detection has gained growing importance for vehicle safety and reliability. For the improvement of reliability, safety and efficiency; advanced methods of supervision, fault detection and fault diagnosis become increasingly important for many automobile systems. Many times, the trial and error approach has been applied to detect the fault and therefore engine may get more damaged instead of getting repaired. To alleviate such type of problem, the idea of sound recording of engines has been suggested to diagnose the fault correctly without opening the engine. In this paper, fault detection of two stroke engine, Hero Honda Passion four strokes and Maruti Suzuki Alto Automobile Engine have been proposed. The objective is to categorize the acoustic signals of engines into healthy and faulty state. Acoustic emission signals are generated from three different automobile engines in both healthy and faulty conditions. The paper proposes soft computing approach for detection of multiple faults in automobile engines which include signal conditioning, signal processing, statistical analysis and Artificial Neural Networks. The Statistical techniques and different Artificial Neural Networks have been employed to classify the faults correctly. Performance of Statistical techniques and ten types of Artificial Neural Networks have been compared on the basis of Average Classification Accuracy and finally, optimal Neural Network has been designed for the best performance.
Keywords: Artificial Neural Network, Automobile Engine, Classification Accuracy, Fault Detection and Stistical Techniques
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #26, pp.254-262
Title of the Paper: An Approach to Accurate Inversion of Convolution Transforms by FIR Filters
Authors: Vairis Shtrauss
Abstract: Inversion of convolution transforms is considered by FIR filters for aperiodic band- and time-unlimited signals from the perspective attaining maximum accurate inverted waveforms with controllable noise amplification of the filter. The difficulties hampering to gain this goal, such as a lack of knowledge how the digital filter shall deviate from ideal one to produce waveforms as accurately as possible, complexity to choose optimal sampling rate, necessity to sacrifice the accuracy for suppressing noise, etc. are analysed. Based on learning in the input-output signal domain and controlling noise amplification by varying sampling rate, an approach is developed for designing maximum accurate filters, which are specified only by two user’s relevant parameters: (i) the desired noise gain and (ii) the continuous time support. Implementation of the approach is illustrated by designing a digital differentiator for the logarithmic derivative and a digital estimator of the distribution of relaxation times. Simulation results are presented demonstrating that the approach allows constructing more accurate FIR filters with predefined noise amplification and support sizes compared with those designed by other commonly used techniques.
Keywords: Convolution Transform, Inversion, Deconvolution, FIR Filter, Accuracy, Noise Amplification, Design by Learning
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #25, pp.242-253
Title of the Paper: Estimation of Multipath Fading Channel Using Fractal Based VSLMS Algorithm
Authors: Anubha Gupta, Shivdutt Joshi
Abstract: This paper evaluates the performance of fractal based variable step-size LMS (FB-VSLMS) algorithm on the estimation of multipath fading channel for nonstationary process transmission. The algorithm exploits the statistics of the nonstationary process and uses non-diagonal step-size matrix to design an adaptive LMS filter in order to estimate slow fading correlated Rayleigh channel, in particular, asymptotically stationary AR channel and Jakes channel. Analytic expressions of steady-state mean-square weight error (MSWE) and optimum step-size parameter are computed for these channels. The analytical expression of optimum step-size would enable reliable channel estimation in real time. Simulation results are compared with analytic expressions developed in this paper and are shown to agree with good conformity.
Keywords: Rayleigh fading channel, channel estimation, variable step-size LMS algorithm, nonstationary signals.
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #24, pp.230-241
Title of the Paper: Motion Estimation based on Artificial Fish-Swarm in H.264/AVC Coding
Authors: Chun Fei, Ping Zhang, Jianping Li
Abstract: Motion estimation plays a key role in H.264/AVC video coding, but it is the most time-consuming task in the encoding process. In order to reduce the computational complexity of motion estimation in H.264/AVC video coding, this paper proposes a new search algorithm based on artificial fish-swarm algorithm (AFSA) which is a new efficient optimizing method. Firstly, some characteristics of AFSA are modified, such as visual, step, moving direction and initial fish positions in order to better adapt to motion estimation. Secondly, an adaptive search strategy based on modified AFSA Algorithm is presented to further reduce computational complexity, including double search mode, dynamic search range and early termination strategy. Experimental results show that the proposed algorithm saves the average motion estimation times up 39.29% and 31.22% for UMHexagonS and EPZS algorithm, which are adopted in H.264/AVC video coding, with almost same rate distortion performance.
Keywords: Motion estimation, artificial fish-swarm, optimizing method, H.264/AVC coding, search mode, rate distortion
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #23, pp.221-229
Title of the Paper: Implementation of Wavelet Based Modified Buyer-Seller Watermarking Protocol (BSWP)
Authors: Ashwani Kumar, S. P. Ghrera, Vipin Tyagi
Abstract: Wavelet based watermarking is a promising technology for embedding the information as an unperceivable signal into the digital contents. The main characteristics of wavelet are wavelets' excellent spatial localization and multi-resolution. Wavelet based modified buyer-seller watermarking protocols integrate multimedia, watermarking techniques, fingerprinting and cryptography for copyright protection, piracy tracing, and privacy protection of the digital content. In this paper we have implemented the wavelet based modified buyer-seller watermarking protocol. Our protocol focuses on managing the watermark. A binary watermarked image that is a logo is embedded in certain selected sub-bands of a 3-level DWT transformed of the original image. Then, the DWT sub - band is computed and the sequences of the watermark bits are embedded in the coefficients of the high frequency sub-bands. The quality of the watermarked image generated with wavelet based method is better, using the same watermark strength. To check the imperceptibility and robustness of the watermarked image, PSNR and NCC parameters are used. Furthermore the algorithm is robust against the various attacks such as JPEG Compression, Rotation, Gaussian Noise, Median Filter and Salt & Pepper Noise.
Keywords: Copyright Protection, Wavelet Transform, Fingerprinting, Cryptography
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #22, pp.212-220
Title of the Paper: Joint Estimation of Angle, Doppler and Polarization Parameters for Narrowband MIMO Multipath Channels Using Polarization Sensitive Antenna Arrays
Authors: Ramoni Adeogun
Abstract: A novel subspace based joint angle of arrival (AOA), angles of departure (AOD), Doppler shifts and polarization states parameter estimation scheme for polarized two-dimensional (2D) double directional MIMO multipath channels is proposed in this paper. A narrowband system with non-polarized uniform linear array at the transmitter and cross-polarized antenna array at the receiver is considered. The proposed algorithm perform a simple transformation on the estimated channel state information (CSI) matrix in such a manner that multidimensional ESPRIT can be utilized to exploit the translational invariance in the angle, Doppler and polarization dimensions. Simulation results show that the proposed algorithm can accurately estimate the AOA, AOD, Doppler shifts and polarization angles of the multipath channel even for closely spaced scattering sources.
Keywords: Polarization, MIMO, Multidimensional ESPRIT, Multipath Parameter Estimation
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #21, pp.205-211
Title of the Paper: Evaluation of Dental Implant Osseointegration Using Ultrasonic Spectrometry: A Phantom Study
Authors: Hamed Hamid Muhammed, Satya V. V. N. Kothapalli
Abstract: One of the challenging and important problems that still needs solution within the field of dental implant surgery is to monitor the osseointegration process. Therefore, this work aims to achieve a reliable noninvasive automatic method to evaluate dental implant stability which is directly related to the grade of osseointegration. For this purpose, an experimental phantom study was performed to simulate this process and evaluate it. Ultrasonic spectrometry was proposed and used to take measurements that were processed and analyzed to estimate the stability of the simulated dental implant. The phantom that was designed and used in the experiments simulated a jawbone with a dental implant and was made of a little pool filled with soft-tissue-equivalent material (with respect to ultrasound waves) and a solid cylinder of fresh oak-wood immersed into it to simulate the jawbone. A metal screw was used to simulate the dental implant. By screwing this screw into or out of the wooden cylinder, varying grades of stiffness and contact between the screw and the wooden tissues were obtained. And by this way, varying screw stability grades which simulate varying osseointegration grades were achieved. Pulse-echo ultrasound was used to measure the power spectra of the received ultrasonic echo-signals. These power spectra were, at first, processed and normalized then analyzed by using the partial least squares method to estimate the corresponding implant stability or stiffness grades. The number of screwing turns (for the screw into or out of the wooden cylinder) was used as a measure of stiffness grade.The feasibility of this approach was investigated through experimental tasks and promising results were achieved. A coefficient of determination R2 of 96.4% and a mean absolute error of ±0.23 screwing turns were achieved when comparing real and estimated stiffness-grade values, indicating the high efficiency and good accuracy of this approach.
Keywords: Screw dental implant stability; stiffness grade; contact grade; partial least squares PLS; pulse-echo ultrasound; spectroscopy; spectral analysis; power spectra
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #20, pp.194-204
Title of the Paper: Bearing-Only Slam: A Fast Algorithm without using Extended Кalman Filter
Authors: D. G. Arseniev, N. A. Berkovskii
Abstract: In this paper a new method for solving 2D Bearing-only SLAM is proposed. We use only Sequential Monte Carlo Methods to estimate current positions of the robot and for determining the landmarks’ coordinates. The main advantages of the proposed method are the high speed and the trivial generalization to 3D case. Our method has linear complexity growth with respect to number of the landmarks.
Keywords: Bearing-only SLAM, Sequential Monte Carlo Methods, Patricle filters, Rao-Blackwellisation method, Fast SLAM
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #19, pp.188-193
Title of the Paper: An Efficient VLSI Computation Reduction Scheme in H.264/AVC Motion Estimation
Authors: Shikai Zuo, Mingjiang Wang, Liyi Xiao
Abstract: The variable block sizes motion estimation in H.264 is key technique to remove inter-frame redundancy. This technique not only requires huge memory bandwidth but also its computation complexity is higher. Therefore, this paper proposes one efficient sub-pixel search algorithm for reducing computation complexity and bandwidth utilization, and a novel VLSI architecture for this algorithm which simplifies variable block sizes motion estimation. The proposed method is efficient compared with those of existing methods which have negative effects on compression, with respect to chip area, operation frequency, and throughput rate. The proposed sub-pixel search architecture decreases the numbers of search pixels of full pixels motion estimation by around 70% and the chip area by around 40% than the others search algorithm. Besides, an optimized motion estimation MV prediction algorithm is used to remove data dependency, and optimization storage policies are used to save hardware resources. The proposed sub-pixel search architecture can work at 200 MHz with 530k gate count, which supports high-definition television 1920×1080 format.
Keywords: Sub-pixel search, systolic array, H.264 encoder, motion estimation, 1080P, HDTV, VLSI
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #18, pp.178-187
Title of the Paper: Target Detection and Tracking for Video Surveillance
Authors: S. Vasuhi, V. Vaidehi
Abstract: Target detection and tracking is an important problem in the automatic surveillance system. This paper proposes a Combined Gaussian Hidden Markov Model based Kalman Filter (CGHMM-KF) scheme for tracking people in multiple camera sensor network for monitoring and tracking of target (person/vehicle) in secured area. To detect the target under different illumination conditions, HMM with Mixture of Gaussians (MoG) is adapted. The MoG estimates the background and detects the foreground and the HMM modeling technique captures the shape of the desired object from the foreground. Finally, tracking of multiple targets is done by Kalman Filter (KF) with a bounding box, indicating the location of the person even with the motion in the background. The area of coverage can be extended dynamically using multiple cameras. The proposed approach provides better detection and tracking of person even in the presence of occlusion, target miss association and multiple persons in the environment.
Keywords: HMM, Kalman Filter, MoG, Multi-camera, Multi-Target
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #17, pp.168-177
Title of the Paper: Image Classification Using Novel Set of Charlier Moment Invariants
Authors: Abdeslam Hmimid, Mhamed Sayyouri, Hassan
Abstract: The use of the discrete orthogonal moments, as feature descriptors in image analysis and pattern recognition is limited by their high computational cost. To solve this problem, we propose, in this paper a new approach for fast computation of Charlier‟s discrete orthogonal moments. This approach is based on the use of recurrence relation with respect to variable x instead of order n in the computation of Charlier‟s discrete orthogonal polynomials and on the image block representation for binary images and intensity slice representation for gray-scale images. The acceleration of the computation time of Charlier moments is due to an innovative image representation, where the image is described by a number of homogenous rectangular blocks instead of individual pixels. A novel set of invariants moment based on the Charlier moments is also proposed. These invariants moment are derived algebraically from the geometric moment invariants and their computation is accelerated using image representation scheme. The proposed algorithms are tested in several well known computer vision datasets, regarding computational time, image reconstruction, invariability and classification. The performance of Charlier invariants moment used as pattern features for a pattern recognition and classification is compared with Hu and Legendre invariants moment.
Keywords: Charlier discrete orthogonal polynomials, Charlier moments, Charlier invariant moments, Image block representation, image slice representation, Fast computation, Image reconstruction, Pattern recognition, classification
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #16, pp.156-167
Title of the Paper: A Real Time Improved Driver Fatigue Monitoring System
Authors: V. Krishnasree, N. Balaji, P. Sudhakar Rao
Abstract: One of the main technical goals in the automotive industry is to provide and increase vehicle safety. The traffic accidents are increasing day by day due to a diminished driver’s vigilance level and it became a serious problem for the society. By monitoring the fatigue of the driver, the vehicle safety can be improved. Eye detection is an important initial step in Driver Fatigue Detection System. This feature can be used for developing ‘Driver fatigue detection system’ by monitoring attention or drowsiness of the driver.
Keywords: Driver fatigue, accident aversion, eye detection, Haar classifier and OMAP processor
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #15, pp.146-155
Title of the Paper: An Efficient Informed Embedding Scheme Using Systematic Nested Block Codes over Gaussian Channel
Authors: Chi-Yuan Lin, Sheng-Chih Yang, Jyun-Jie Wang, Cheng-Yi Yu
Abstract: We present a high-capacity informed embedding scheme based on a trellis structure for a nested linear block code. This scheme can embed adaptive robust watermarked messages for various applications. Instead of using randomly generated reference vectors as arc labels, this scheme uses the codewords of a nested block code to label the arcs in the trellis structure so that each codeword can carry different amounts of hidden payload. The proposed algorithm attempts to achieve two objectives: first, to minimize the modified position for each watermarked image; second, to perform the proposed embedding algorithm to minimize the amplitude distortion for these modified positions. Additionally, the proposed algorithm can perform iteration to determine a tradeoff between robustness and fidelity using numerous controllable parameters. Finally, the experimental results report the robustness and fidelity performance of this algorithm in AWGN attack channels. The experiment also simulates computational complexity and the proposed section-based informed embedding, which requires less operational complexity compared with Miller’s informed embedding.
Keywords: Data hiding, Informed embedding, Digital watermarking, Robustness
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #14, pp.136-145
Title of the Paper: Detection and Segmentation Text from Natural Scene Images Based on Graph Model
Authors: Xiaopei Liu, Zhaoyang Lu, Jing Li, Wei Jiang
Abstract: This paper presents a new scheme for character detection and segmentation from natural scene images. In the detection stage, stroke edge is employed to detect possible text regions, and some geometrical features are used to filter out obvious non-text regions. Moreover, in order to combine unary properties with pairwise features into one framework, a graph model of candidate text regions is set up, and the graph cut algorithm is utilized to classify candidate text regions as text or non-text. As for segmentation, a two-step technique for scene text segmentation is proposed. Firstly, the K-Means cluster algorithm is employed in color RGB and HSI color space respectively, and the better result is selected as initial segmentation. Then in minimum energy framework, graph cut is employed for re-labeling verification. Experimental results show the satisfactory performance of the proposed methods.
Keywords: Scene text detection, text segmentation, stroke width, Hog feature, Graph model
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #13, pp.124-135
Title of the Paper: Comparative Analysis of PCA and Wavelet based Motion Artifact Detection and Spectral Characterization in W-ECG
Authors: Rahul Kher, Tanmay Pawar, Vishvjit Thakar
Abstract: The use of wearable ECG recorders is becoming common nowadays for the people suffering from cardiac disorders. Although it is a convenient option for hospitalization, it has an inherent drawback of recorded ECG being contaminated by motion artifacts due to various body movement activities of the wearer. In this paper, the spectral characteristics of motion artifacts occurring in wearable ECG (W-ECG) signals have been studied using principal component analysis (PCA) and wavelet transform. The residuals of PCA and wavelet transform characterize the spectral behaviour of the motion artifacts occurring in W- ECG signals. The ECG signals have been acquired from Biopac MP-36 system and a self-developed wearable ECG recorder. The performance is evaluated by power spectral density (PSD) plots of PCA residual errors as well as statistical parameters like mean, median and variance of PCA and wavelet residuals. The PSD plots indicate that the peak frequency of the motion artifacts occurring due to various body movements (like left arm up-down, right arm up-down, left and right legs up-down, waist twist, walking and sitting up-down) is located around 5-15 Hz, coinciding with the ECG spectrum.
Keywords: Wearable ECG (W-ECG), PCA, Wavelet transform, Motion artifacts, PSD
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #12, pp.116-123
Title of the Paper: Implementation of Laser Simulator Search Graph Approach for Detection and Path Planning in Roundabout Environments
Authors: Mohammed A. H. Ali, Musa Mailah, Tang Howe Hing
Abstract: In this paper, a Laser simulator search graph approach for free-path search graph in complex unstructured environments has been developed and implemented for a robust mobile robot navigation system through the roundabout environments settings. The principle and methodology of laser simulator approach was clearly presented and explained for visibility searching of the optimum path in unknown environments with existence of some motion constraints and rules. The proposed approach gives the possibility for mobile robot to effectively track the path when countering a roundabout with and without obstacle and considering a number of scenarios. The algorithm is applied into tow kinds of setup: first it is simulated using MATLAB with the grid map used to create the road roundabout environment and select the path according to the respective road rules. Secondly it is used to recognize the roundabout in the real roundabout from sequence of images and enable the mobile robot for making decision process. From the results, it is verified that the performance of the proposed approach is excellent and that the mobile robot is able to track the best path from the selected start position to the goal point even in the presence of the obstacles.
Keywords: Path Planning, Free-Collision Search Path, Laser Simulator (LS), Road Roundabout, Road Curbs, MATLAB
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #11, pp.106-115
Title of the Paper: A Particle Swarm Optimization based Support Vector Machine for Digital Communication Equalizers
Authors: Zey-Ou Li, Chi-Wen Li, Ying-Ren Chien
Abstract: The support vector machine (SVM) is a powerful tool for solving problems with high dimensional, nonlinearly, and is of excellent performance for channel equalization in communication systems. In this study, we propose PSO-SVM as channel equalization. To reconstruct the signal that has the inter symbol interference (ISI) and white Gaussian noise which in high speed communications environments. The SVM parameters will affect the identification of the result. Therefore, we use particle swarm optimization (PSO) to find the suit parameters in SVM. The PSO-SVM to realize the Bayesian equalization solution can be achieved efficiently.
Keywords: Support vector machine, particle swarm optimization, channel equalization
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #10, pp.95-105
Title of the Paper: Least Square Support Vector Machine based Multiclass Classification of EEG Signals
Authors: Deepesh Kumar, Rajesh Kumar Tripathy, Ashutosh Acharya
Abstract: This paper describes the pattern recognition technique based on multiscale discrete wavelet transform(MDWT) and least square support vector machine (LS-SVM) for the classification of EEG signals. The different statistical features are extracted from each EEG signal corresponding to various seizer and nonsiezer brain functions, using MDWT. Further these sets of features are fed to the LS-SVM multiclass classifier for the classification. At the output, the required classifier predicts the output level corresponding to the given test features. The actual output levels are compared with the classifier’s predicted output levels and the performance of classifier determined using classification rate (CR). The outcome of our result confirms that the LS-SVM multiclass classifier with linear kernel function, “One VS All” coding algorithm and 10 fold cross validation scheme gives better performance in terms of CR of 98.07% than other algorithm based LS-SVM multiclass classifier for the required EEG signal classification.
Keywords: Electroencephalogram (EEG), multiscale discrete wavelet transforms (MDWT), statistical features, least square support vector machine (LS-SVM), RBF kernel, Linear Kernel, Polynomial kernel, Classification rate (CR)
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #9, pp.86-94
Title of the Paper: Linear Filtering and Modelling based on Gram-Schmidt Orthogonalization Concept
Authors: B. Yagoubi
Abstract: In this work, the approach we suggest for the linear filtering consists in considering any linear filter as a geometric hyper plane space to which the output signal vector belongs. Any signal orthogonal component to this space vanishes. So removing a non desired component from a signal is to look for a flat space to which this component is orthogonal; in other words, this non desired component will not be observed by orthogonal projection in this geometric space or it does not belong to it and hence, it is eliminated according to Gram-Schmidt orthogonalization concept. To clarify this point view, we compare this geometric filtering procedure to that of an ideal low pass filter in Fourier space and show that it is simple, more efficient and general than the traditional filtering. As an application, we extend this geometric filtering to the linear modelling by eliminating the modelling error, considered as a non-desired output signal component, in order to determine the model coefficients in the case of a linear modelling, linear model identification, and auto-regressive modelling. In addition, using Pythagoras theorem, we calculate the modelling error variance which can be used for testing the linear model approximation quality.
Keywords: Geometric linear filtering; Gram-Schmidt orthogonalization; orthogonal component; geometric hyper plane; linear model; auto-regressive model
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #8, pp.75-85
Title of the Paper: Research on Aerial Flyer Interception Based on Anti-Aircraft Gun System
Authors: Liu Heng, Mei Wei, Shan Gan Lin
Abstract: In order to satisfy the requirements of anti-terrorism and security task, the interception methods of aerial flyer has been got much attention. According to the problem of low effectiveness-cost ratio of interception by missile traditionally, the feasibility of interception by anti-aircraft gun system is researched in the paper, two new interception methods, the point interception and barrage net interception are presented. The conception and idea of the two interception modes are proposed, and the maneuverability of the latter mode is validated by using probability theory. Finally, the validity of the two modes is verified through simulation. Results show that, point interception mode can be adopted when forecasting precision of aerial flyer is high, and barrage net mode can be used is applied in the condition of low forecasting precision, and the relationships between the two modes are not mutually exclusive and they are complementary.
Keywords: Anti-aircraft gun system; Point interception; Barrage net interception; Probability Theory; research
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #7, pp.65-74
Title of the Paper: Acoustic Signal based Traffic Density State Estimation using Adaptive Neuro-Fuzzy Classifier
Authors: Prashant Borkar, L. G. Malik, M. V. Sarode
Abstract: Traffic monitoring and parameters estimation from urban to battlefield environment traffic is fast-emerging field based on acoustic signals. This paper considers the problem of vehicular traffic density state estimation, based on the information present in cumulative acoustic signal acquired from a roadside-installed single microphone. The occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) are determined by the prevalent traffic density conditions on the road segment. In this work, we extract the short-term spectral envelope features of the cumulative acoustic signals using MFCC (Mel-Frequency Cepstral Coefficients). The (Scaled Conjugate Gradient) SCG algorithm, which is a supervised learning algorithm for network-based methods, is used to computes the second-order information from the two first-order gradients of the parameters by using all the training datasets. Adaptive Neuro-Fuzzy classifier is used to model the traffic density state as Low (40 Km/h and above), Medium (20-40 Km/h), and Heavy (0-20 Km/h). For the developing geographies where the traffic is non-lane driven and chaotic, other techniques (magnetic loop detectors) are inapplicable. Adaptive Neuro-Fuzzy classifier is used to classify the acoustic signal segments spanning duration of 20–40 s, which results in a classification accuracy of 93.33% for 13-D MFCC coefficients and around 96% when entire features were considered, 77.78% for first order derivatives and ~75% for second order derivatives of cepstral coefficients.
Keywords: Acoustic signal, Noise, Traffic, Density, Neuro-Fuzzy
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #6, pp.51-64
Title of the Paper: Wavelet-Based Image Compression System with Linear Distortion Control
Authors: Je-Hung Liu, King-Chu Hung
Abstract: In this paper, an optimized quantization of wavelet transform coefficients and low complex distortion control system for image compression is proposed. Distortion control is an important issue in maintaining the desired quality in the retrieved signal of compressed data. We construct a linear relationship between the distortion and quantization scale, which is crucial for efficient quality maintenance due to its simplicity and accuracy. This method can provide wavelet-based image data compression with a precise linear prediction model, resulting in high compression performance. A genetic algorithm (GA) is used to optimize the indices of distortion and compression ratio (CR). The optimization can induce linear relationships among multi-level quantization scales and enable the control of multi-level quantization scales with a single variable. Then a curve fitting technique is used to produce the quantization scales formula which is controlled by a single value. The experimental results showed that the proposed method can obtain better compression performance and distortion control exactly as predicted, with low complexity.
Keywords: Distortion control, genetic algorithm, image coding
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #5, pp.41-50
Title of the Paper: Decomposition of 3D Medical Image based on Fast and Adaptive Bidimensional Empirical Mode Decomposition
Authors: Omar Ait Zemzami, Hamid Aksasse, Mohammed Ouanan, Brahim Aksasse, Aziza Benkuider
Abstract: Three-dimensional (3D) imaging and display have been subjects of much research due to their diverse benefits and applications. This paper presents a new approach for decomposing the three-dimensional medical images using Bidimensional Empirical Mode Decomposition (BEMD). The BEMD is an extension of the Empirical Mode Decomposition (EMD), which can decompose non-linear and non-stationary signals into basis functions called the Intrinsic Mode Functions (IMFs). IMFs are monocomponent functions that have well defined instantaneous frequencies. This decomposition, obtained by a process known as sifting process, allows extracting the structures at different scales and spatial frequencies with modulation in amplitudes and frequency. BEMD decomposes an image into bidimensional BIMFs. This paper suggests a simple, but effective, method for decomposing a three-dimensional medical image into basis function. This approach is neither parametric nor data driven, which means it does not depend on a priori basis set. Moreover, it preserves the totality of information in term of the quality of the reconstructed 3D image. The performance of this approach, using the BEMD, is approved with some medical images.
Keywords: Bidimensional Empirical Mode Decomposition (BEMD), Fast and Adaptive BEMD (FABEMD), Intrinsic Mode Function (IMF), 3D Reconstruction
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #4, pp.30-40
Title of the Paper: An Investigation on the Performance of Hybrid Features for Feed Forward Neural Network Based English Handwritten Character Recognition System
Authors: J. Pradeep, E. Srinivasan, S. Himavathi
Abstract: Optical Characters Recognition (OCR) is one of the active subjects of research in the field of pattern recognition. The two main stages in the OCR system are feature extraction and classification. In this paper, a new hybrid feature extraction technique and a neural network classifier are proposed for off-line handwritten English character recognition system. The hybrid features are obtained by combining the features extracted using diagonal, directional, Principal Component Analysis (PCA) techniques along with statistical and geometry feature extraction technique. The hybrid features are used to train a feed forward back propagation neural network employed for performing classification tasks. The hybrid features derived from two hundred character sets of lowercase English alphabets (a to z) were used for training the network. The overall recognition system has been tested extensively and shown to perform better than individual feature extraction techniques. The hybrid technique suitably combines the salient features of the handwritten characters to enhance the recognition accuracy.
Keywords: Handwritten English character recognition, image processing, hybrid feature extraction, neural network classifier
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #3, pp.21-29
Title of the Paper: Comparative Study of Deconvolution Algorithms for GPR Bridge Deck Imaging
Authors: I. Abdel-Qader, V. Krause, F. Abu-Amara, O. Abudayyeh
Abstract: Bridge decks deteriorate over time as a result of freezing-and-thawing, heavy use, and water penetration resulting in internal defects. Ground penetrating radar (GPR) can be used as a non-destructive method for detecting such defects. Unfortunately, reflections from closely spaced objects overlap which prevents the accurate estimation of the round-trip travel time of GPR waves to the closely spaced objects. In this paper, singular value decomposition (SVD), subset selection (SSDA), and independent component analysis (ICA) deconvolution algorithms are used to solve this problem using GPR scans of simulated concrete bridge decks. Then, velocity analysis method is used to estimate depth of defects as an evaluation criterion. Results show that ICA has better performance than SVD and SSDA at a cost of slower execution time.
Keywords: Singular value decomposition, subset selection deconvolution algorithm, independent component analysis, ground penetrating radar, bridge condition assessment, non-destructive testing
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #2, pp.9-20
Title of the Paper: An Adaptive Image Denoising Method based on Thresholding
Authors: Hari Om, Mantosh Biswas
Abstract: This paper proposes an Adaptive Image Denoising Method based on Thresholding that follows the similar approach as in the NeighShrink method. This method shrinks the noisy wavelet coefficients using an adaptive threshold. The NeighShrink and its versions namely, IAWDMBNC and IIDMWT always produce unfavourable smoothing of edges and details of the noisy image because these methods kill more noisy coefficients during the shrinkage. Our proposed method overcomes these drawbacks and performs better than the NeighShrink, IAWDMBNC, and IIDMWT in terms of Peak Signal-to-Noise Ratio (PSNR) using shrinkage based on our proposed threshold.
Keywords: Image Denoising, Thresholding method, Coefficient, Peak Signal-to-Noise Ratio (PSNR)
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 10, 2014, Art. #1, pp.1-8