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WSEAS Transactions on Signal Processing


Print ISSN: 1790-5052
E-ISSN: 2224-3488

Volume 11, 2015

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 11, 2015


Title of the Paper: New Method for Measuring the Detail Preservation of Noise Removal Techniques in Digital Images

Authors: Fabrizio Russo

Abstract: It is known that cancelling the noise without blurring the image details is a very difficult task for any image denoising technique. The availability of metrics for accurate evaluation of filtering distortion is thus of paramount importance for the development of new filters. Peak signal-to-blur ratio PSBR is a recently introduced measure of detail preservation that overcomes the limitations of the sole peak signal-to-noise ratio (PSNR) and other metrics in evaluating the performance of image denoising filters. Formally, the PSBR is the PSNR component that deals with the detail blur, so the method that is adopted for blur estimation plays a key role. This paper presents a novel algorithm for PSBR computation that offers significant advantages over the first method: it is simpler, more robust and much more accurate. Furthermore, this paper presents new validation tools for evaluating the accuracy of this kind of metrics when some well known classes of linear and nonlinear filters are considered. Results of many computer simulations dealing with images corrupted by different combinations of Gaussian and impulse noise show that the proposed PSBR algorithm outperforms the most effective metrics in the field.

Keywords: Image filtering, image denoising, Gaussian noise, impulse noise, image quality, PSNR

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #38, pp. 317-327


Title of the Paper: An Optimization Method for Numerically Solving Three-Point BVPs of Linear Second-Order ODEs with Variable Coefficients

Authors: Ming Hou, Liya Fan

Abstract: It is known that most numerical methods for solving differential equations are based on iterative methods or Taylor expansion methods. This paper tries to study a numerical method from a new perspective?optimization method. By means of the idea of kernel ε-SVR, the paper constructs an optimization model for a class of threepoint boundary value problems (BVPs) of linear second-order ordinary differential equations (ODEs) with variable coefficients and proposes a novel numerical method for solving them. The proposed method has a certain versatility and can be used to solve some other kinds of differential equations and integral equations. In order to verify the effectiveness of the proposed method, comparative experiments with six specific linear second-order ODEs are performed. Experimental results show that the proposed method has a good approximation property.

Keywords: Optimization modeling, numerical method, ordinary differential equation, kernel "-support vector regression, Lagrange function

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #37, pp. 310-316


Title of the Paper: An Algorithm for Indoor Photo Diode-Based Visible Light Positioning

Authors: Xiang Zhao, Jiming Lin

Abstract: In recent years, indoor visible light positioning using white LEDs is getting more attention. An algorithm for indoor photo diode-based visible light positioning is proposed, where the time difference of arrival of the received signal, together with the scale and azimuth angle of the receiver is used to determine the location of the receiver. Hyperbola or straight line equations are established and the crossing point of these equations determines the location of the receiver. In a moderate model room, the performance of the proposed algorithm is demonstrated through simulation, with the positioning accuracy usually in the order of millimeters, suitable for various indoor location-based services.

Keywords: indoor positioning system, visible light, photo diode, white LEDs, time difference of arrival, scale, azimuth angle

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #36, pp. 304-309


Title of the Paper: The Phase Ambiguity Resolution by the Exhaustion Method in a Single-Base Interferometer

Authors: Yury Fateev, Dmitry Dmitriev, Valery Tyapkin, Vladimir Shaydurov

Abstract: In the paper, the phase methods are considered for the measurement of the spatial orientation of an object by means of satellite navigation equipment. Methods for the resolution of phase ambiguity are analyzed. Effectiveness and applicability of the one-step methods are discussed in more detail. It is proved that for the realization of the exhaustion method the minimal group of navigation spacecrafts should include 5–6 observed ones. When measuring signals of 8 spacecrafts of base length 1 m, an unambiguous solution is achieved practically in all cases.

Keywords: Satellite navigation, spatial orientation, resolution of phase ambiguity

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #35, pp. 296-303


Title of the Paper: Edge Enhanced and Nonlocal Sparse Representation for Image Denoising

Authors: Qian Wang, Ping Wang, Yuwei Zang

Abstract: Sparse representation and nonlocal self-similarity play an important role and show better results in image denoising. However, the methods based on sparse representation or nonlocal self-similarity tend to smooth the image edge structures or generate some artifacts. To improve the performance of image denoising, in this paper we propose an edge enhanced and nonlocal sparse representation (ENSR) model which combines Sobel edge detection results, local sparsity and nonlocal self-similarity. We use the iterative shrinkage algorithm to solve the l1-regularized ENSR minimization problem. The experimental results show that ENSR can better preserve the edge structure and achieve a competitive PSNR performance compared with some existing methods.

Keywords: Image denoising, Sparse representation, Sobel operator, Nonlocal self-similarity

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #34, pp. 288-295


Title of the Paper: The Two-Step Non-Data-Aided SNR Estimation in the Low SNR Region of OFDM Signals

Authors: Dong Wang, Wei Xu

Abstract: In this paper, a novel two-step non-data-aided (NDA) signal to noise ratio (SNR) estimator is proposed to improve its accuracy in the low SNR region of orthogonal frequency division multiplexing (OFDM) signals. The two-step estimator consists of a coarse estimation followed by a refinement step. In the first step, three linear independent coarse estimations of the signal and noise power are obtained by exploring the cyclic-prefix (CP)-induced redundancy. In the second step, these three coarse estimations are refined by resorting to the best linear unbiased estimator (BLUE). Compared with the schemes which only rely on two out of these three coarse estimations, a more accurate SNR estimation can be obtained in the low SNR region. Simulation results show that the proposed noise and signal power estimator achieve approximately 6dB and 2dB SNR gain respectively in the low SNR region, therefore, the proposed SNR estimator provides approximately 4dB SNR gain.

Keywords: Low SNR, non-data-aided, OFDM, SNR estimation

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #33, pp. 280-287


Title of the Paper: HEVC vs. H.264/AVC Standard Approach to Coder’s Performance Evaluation

Authors: Zoran Milicevic, Zoran Bojkovic, Kamisetty R. Rao

Abstract: The H.264/AVC standard achieves much higher coding efficiency than the H.263, MPEG-2 and MPEG-4 standard, due to its improved inter and intra-prediction modes at the expense of higher computation complexity. Throughout the evolution of video coding standards, continued efforts have been made to maximize compression capability and improve other characteristics such as data loss robustness, while considering the practical computational resources. On the other hand, High Efficient Video Coding (HEVC) standard can provide a significant amount of increased coding efficiency compared to previous H.264/AVC standard. The features of the new design provide approximately a 50% bit-rate savings for equivalent perceptual quality relative to the performance of prior standard (especially for a high-resolution video). In order to compare the performance and complexity without significant rate-distortion performance degradation, the two different HEVC coders vs. H.264/AVC coder are tested for the fixed Quantization Parameter (QP) value, when Main profile, appropriate motion vector (MV) search ranges and IPPP structures are used. Simulation results have shown that the bit-rate was reduced over 50%, while the encoding time saving is slightly decreased up to 16% depending on the tested video sequence, when reference HEVC software’s HM-14.0 and HM-15.0 are compared to reference H.264/AVC software JM 18.6. However, there was negligible loss in term Signal-to-Noise Ratio (SNR).

Keywords: H.264/AVC standard, HEVC standard, Encoding time saving, Signal-to-noise ratio, Bit-rate reduction

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #32, pp. 272-279


Title of the Paper: Learning One-class KSVM+ for Multi-class Problems with Group Information of Data

Authors: Wensong Zhao, Liya Fan

Abstract: This paper is denoted to study the effect of the group information of data in one-class kernel support vector machines (OC-KSVMs) for classification accuracy and time consumed of multi-class classification data. Two new classification methods based on OC-KSVMs are presented. One is OC-KSVM with maximum margin from the origin and group information of data (briefly, MMOC-KSVM+) and another is OC-KSVM with hypersphere and group information of data (briefly, HSOC-KSVM+). We proved theoretically that MMOC-KSVM and HSOC-KSVM are equivalent for Gaussian RBF kernels. Experiments on three real-words data sets are performed in order to test and evaluate the efficacy of the proposed methods. Experimental results indicate that the group information of data can improve the classification accuracy of data and meanwhile increase the time consumed of algorithms.

Keywords: multi-class classification problem, One-class kernel SVM, group information of data, maximum margin, hyper-sphere

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #31, pp. 262-271


Title of the Paper: Outage Analysis in Multi-User and Multi-Relay Cognitive AF Relaying Networks Using MRC

Authors: Jing Yang, Lei Chen, Caihong Xu, Jie Ding, Yuren Du

Abstract: This paper investigates the outage performance in multi-user and multi-relay cognitive amplify-andforward relaying networks for MinW relay selection scheme over independent non-identically distributed Rayleigh fading channels, where the eavesdropper node may intercept the source message. To guarantee the quality-ofservice of the primary user (PU), both the maximum tolerable peak interference power at the PU and maximum allowable transmit power at secondary users are considered. Relay selection is employed in this paper to improve the secure transmission from secondary source to secondary destination by minimizing instantaneous signal-tonoise ratio at the eavesdropper. For the considered relay selection scheme, we analyze its outage performance and obtain the closed-form lower and upper bounds as well as asymptotic expressions for reliability outage probability (OP) with maximal ratio combining utilized. From the asymptotic expressions, it can be observed that the diversity gain of OP equals to N + 1, where N is the number of secondary destinations. Finally, Monte-Carlo simulations are presented to validate our analysis results.

Keywords: Outage probability, amplify-and-forward, cognitive relaying networks, relay selection, maximal ratio combining

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #30, pp. 255-261


Title of the Paper: Image Cryptosystem Based on Digital Signature and Double Random Phase Encoding

Authors: Hayam Abdel-Mordy, Emad S. Hassan, Sami A. El-Dolil, Fathi E. Abd El-Samie

Abstract: This paper presents a new technique of multi-level security for image transmission based on image signature by Discrete Cosine Transform (DCT2) and image encryption by Double Random Phase Encoding (DRPE). This technique is implemented in two successive steps to enhance the security level of the transmitted image. The proposed technique exploits the benefits of signature and encryption, which make it robust to image processing attacks such as speckle, impulsive and Gaussian noise. Several experiments have been carried out to test the performance of the proposed technique in the terms of Peak Signal-to-Noise Ratio (PSNR), processing time and correlation coefficients. The obtained results show that, the proposed technique enhances the security level of the transmitted images with better immunity to noise when compared to stand-alone signature or DRPE.

Keywords: Digital image signature, Discrete Cosine Transform (DCT), Image encryption, Double Random Phase Encoding (DRPE)

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #29, pp. 245-254


Title of the Paper: Dynamic Population Adaptive Particle Swarm Optimized Particle Filter for Integrated Navigation

Authors: Zhimin Chen, Yuming Bo, Yuanxin Qu, Xiaodong Ling, Xiaohong Tao, Yong Liu

Abstract: Particle filter based on particle swarm optimization algorithm (PSO-PF) is not precise and trapping in local optimum easily, it is not able to satisfy the requirement of advanced integrated navigation system. In order to solve these problems, a novel particle filter algorithm based on dynamic neighborhood population adaptive particle swarm optimization (DPSO-PF) is presented in this paper. This new particle filter can dynamically adjust the particle neighborhood environment, wherein each particle can adjust the number of particles in the neighborhood based on self-adaptation basis according to the neighborhood environment and their own position information, accordingly a best balance is achieved between optimal seeking and convergence rate. Finally different models are used for simulation experiment and the results indicate that this new algorithm improves the precision of GPS/INS integrated navigation system.

Keywords: dynamic, particle filter, integrated navigation, neighborhood, population

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #28, pp. 235-244


Title of the Paper: The Cramer-Rao Bound for 3-D Frequencies in a Colored Gaussian Noise

Authors: Chawki Youness, El Asnaoui Khalid, Ouanan Mohammed, Aksasse Brahim

Abstract: Estimation of model parameters (3-D frequencies), based on the high resolution spectral analysis methods known by their performances and their precision such as 3-D ESPRIT, remains a problem which is essential in the modeling of the signals by a sum of 3-D complexes exponential (3-D SCE model) embedded in an additive gaussian noise. Indeed, good results are obtained when the noise is white and by using the Second Order Statistics (autocorrelations), but if it becomes colored, the results are degraded which forces us to remedy this problem, to think about the Higher Order Statistics (cumulants). To verify the efficiency of estimators of 3-D frequency, we calculate the asymptotic Cramer-Rao Bound (CRB).

Keywords: Spectral Analysis, High Resolution, 3-D ESPRIT, Second Order Statistics, Higher Order Statistics, Fourth Order Cumulant, Cramer-Rao Bound

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #27, pp. 227-234


Title of the Paper: A Damage Identification Method for Messenger Wire in Electrified Railway Based on Improved Synergetics

Authors: Hong Xiaobin, Ni Lei, Luo Zongqiang

Abstract: Facing the problem of damage identification of messenger wire in the complex environment, a damage identification method for messenger wire in electrified railway based on improved Synergetics is put forward. Firstly, the method establishes a preliminary recognition mechanism, which includes the kinetic process of damage recognition, the development of cooperative identification model and the features extraction for messenger wire. Subsequently, this paper introduces the feedback identification mechanism combined by features evaluation and eigenvector reconstruction processes, which can be used to rise the correct rate of recognition. The experiment results showed that in the disturbance and noisy rich environments, the proposed method can identify different depths of cracks well, and the correct rate of recognition has risen to 100% when the feedback identification mechanism is introduced. This proposed approach not only demonstrates a strong ability to reject noise and disturbance, but also overcomes some shortcomings, such as the requirement of massive samples, being vulnerable to environments. Therefore, it will lay the foundation for the structure damage identification in the other more complex environments.

Keywords: Synergetics, Messenger wire, Damage Identification, Feedback Mechanism

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #26, pp. 218-226


Title of the Paper: Comparisons between Sub-Pixel Estimation Techniques in H.264/AVC and VC-1 Video Coding Standards

Authors: Wissal Hassen, Mbainaibeye Jérôme, Hamid Amiri

Abstract: The VC-1 is an advanced video standard developed by Microsoft, while the H.264/AVC is developed by the ITU-T Video Coding Experts Group together with the ISO/IEC JTC1 Moving Picture Experts Group. Both standards use advanced techniques of compression to reduce redundancies in a video sequence. Although the Motion Estimation technique plays a fundamental role to reduce the temporal redundancy, it is still not enough in the case of small Motion Estimation. To ensure a good temporal prediction, some video standards propose a technique of Fractional or Sub-pixel Motion Estimation. This paper shows the efficiency of this technique, it presents the used algorithms in these standards and discusses the effectiveness of each one. Comparisons are made by using two video quality assessment metrics as well as a visual evaluation. The computation time, which is fundamental for real time transmission, in experimental results is also an important evaluation criterion in this work.

Keywords: Block-matching, H.264/AVC standard, image interpolation, image quality assessment, Fractional Motion Estimation, VC-1 standard, video coding

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #25, pp. 204-217


Title of the Paper: Improved Gaussian Mixture PHD Smoother for Multi-Target Tracking

Authors: Xiangyu He, Guixi Liu

Abstract: The Gaussian mixture probability hypothesis density (GM-PHD) smoother proposed recently can yield better state estimates than the GM-PHD filter. However, there are two major problems with it. First, the smoothed PHD distribution can not provide a more accurate target number estimate due to the target number estimation bias becoming larger by smoothing. Second, the computational complexity of computing the smoothed PHD distribution increases with the cardinality of measurement set, which can be very time-consuming when the clutter rate is high. To solve these problems an improved GM-PHD smoother is proposed that improves the target number estimation performance by using the estimated target number of forward GM-PHD filter and reduces the computational cost of GM-PHD smoother by the rectangular gating method. Simulated results show that the improved GM-PHD smoother is superior to the GM-PHD smoother in both the aspects of target number estimate and computational cost, so this improved GM-PHD smoother will have an applicable potential in related fields.

Keywords: Gaussian Mixture, Probability Hypothesis Density, Filtering, Smoothing, Target Tracking, Random Finite Set, Sequential Monte Carlo

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #24, pp. 196-203


Title of the Paper: High Performance Steganographic Scheme Applying Time-Varying Convolutional Embedding Codes

Authors: Chi-Yuan Lin, Jyun-Jie Wang

Abstract: A matrix embedding code was developed as a commonly used steganographic technique in which a parity-check matrix is used to perform embedding. However, a drawback of high decoding complexity for linear block codes by using the maximum-likelihood algorithm is unrealistic. This paper proposes a simple and effective trellis embedding scheme for binary messages. Compared with a matrix embedding algorithm that uses linear block codes, the proposed scheme is more appropriate for embedding messages in the case of linear block codes with a long length. The proposed algorithm uses time-varying convolutional codes as the embedding method and yields a favorable structure of time-varying convolutional codes for steganography. The proposed method employs maximum-likelihood decoding based on trellis construction to identify the coset leader of convolutional codes for large payloads. The experimental results show that the embedding efficiency of the proposed scheme is substantially superior to that of the scheme using linear block codes.

Keywords: Steganography, matrix embedding, embedding efficiency, linear block code, convolutional codes

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #23, pp. 186-195


Title of the Paper: Multi-Information Fusion and Filter Study of Multi-Sensor Velocity Measurement on High-Speed Train

Authors: Hou Tao, Niu Hongxia

Abstract: For the rapid development high-speed railway system, improvement approach of the velocity measurement accuracy has been studied based on multiple speed sensors on high-speed train. In this method, the velocity measurement data from multi-channel speed sensors were dealt through data fusion of arithmetic mean filter, weighted arithmetic mean filter, Federated Kalman filter and adaptive Federated Kalman filter algorithm. On this basis, the comparative study was carried out both at high speed and at low speed based on weighted average algorithm, and algorithm of Federated Kalman filter and adaptive Federated Kalman filter were designed. Discussing the adaptive Federated Kalman filtering problem that four channel sensors are normal and one of sensors is faulted. Then simulation parameters and coefficients were set according to the algorithm and simulated in MATLAB. The results show that it can achieve better fusion effect base on Federated Kalman filter and adaptive Federated Kalman filter algorithm. And the adaptive Federated Kalman filter algorithm is applied to high-speed train system, which has improved the velocity measurement accuracy and fault tolerance, and made the high-speed railway system has better adaptability and improve the train’s operating efficiency based on controlling trains safely running.

Keywords: rail transportation, high-speed train, velocity measurement accuracy, information fusion, Kalman filter

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #22, pp. 178-185


Title of the Paper: Closed Form Delay/Doppler/Propagation Factor Acquisition for GPS Signals

Authors: Yazeed Al-Kharabsheh, Mohammad Amin, Saleh O. Al-Jazzar

Abstract: In this article, a delay/Doppler/propagation factor acquisition method for global positioning system (GPS) signal is proposed. Utilising the Fourier transform (FFT) of the autocorrelation function (ACF) for the received signal, together with some mathematical simplifications, a closed form solution is derived to estimate the delay/Doppler/propagation factor for the received signal. Unlike previous related estimation methods for this case, the proposed method has the advantage of not requiring any searching over the different parameters to perform the estimation. Simulation results for the proposed method are presented in this article to assess its performance.

Keywords: GPS, Acquisition, autocorrelation function, Signal Processing

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #21, pp. 174-177


Title of the Paper: GPS Signal Joint Acquisition Method of Mean Function and Autocorrelation Function under Multiplicative and Additive Noise

Authors: Chao Wu, Luping Xu, Hua Zhang

Abstract: GPS signal detection method based on high order cyclostationarity (DMHOC) is the state-of-the-art method for acquiring the GPS signal under multiplicative and additive noise. However, since the method only uses autocorrelation function to obtain the peak and estimate the received signal frequency, the peak may be buried in the noise when power spectrum of the multiplicative noise (PSMN) is low. To solve the problem, the GPS signal joint acquisition method of mean function and autocorrelation function under multiplicative and additive noise has been proposed. The proposed method uses the energy ratio threshold to determine which function (mean function or autocorrelation function) to be used for estimation of the received signal frequency. The simulation results show that the proposed method is more robust to the change of multiplicative noise than DMHOC.

Keywords: GPS acquisition, Cyclostationarity, Multiplicative and additive noise, Mean function, Autocorrelation function, Energy ratio

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #20, pp. 164-173


Title of the Paper: MRI Image Reconstruction Research Based on Discrete Shearlet Transform

Authors: Xu Hong

Abstract: The two-dimensional wavelet transform for magnetic resonance imaging (MRI) does not represent sparsely curve singularity characteristics, it can only capture the limited direction information. In order to solve this problem, a new method for compressed sensing MRI (CS-MRI) is presented based on discrete shearlet transform in this paper. Frequency coefficients can be got at all scales and in all directions after discrete shearlet transform of MRI image. Then orthogonal matching pursuit algorithm is adopted to recover the sparsing coefficients. Finally, the reconstructed image is getten by inverse shearlet transform. Experimental results show that compared with wavelet transform, discrete shearlet transform for CS-MRI improves quality of reconstructed image and preserves more information about texture and edge.

Keywords: discrete shearlet transform, compressed sensing (CS), MRI image’s reconstruction, sparse expression, feature extraction

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #19, pp. 157-163


Title of the Paper: A Study on Modeling of Road Pavements Based on Laser Scanned Data and a Novel Type of Approximating Hermite Wavelets

Authors: Boris M. Shumilov, Andrey N. Baigulov

Abstract: The paper presents a new system of Hermite basic spline-wavelets of any odd degree, realizing orthogonal conditions to all polynomials up to the same degree. Construction and inverting of the block of filters are considered according to processing of regular signals and three-dimensional fields. The problems of modeling automobile road pavements using laser scanned data are described. The results of numerical experiments and imposing of the designed road onto the processed laser points are also presented.

Keywords: Laser scanning, Data processing, Wavelets, Roads modeling

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #18, pp. 150-156


Title of the Paper: Existence and Exponential Stability of Anti-periodic Solutions for a Cellular Neural Networks with Impulsive Effects

Authors: Changjin Xu, Xinliao Mao

Abstract: In this paper, a cellular neural networks with impulsive effects is investigated. By using differential inequality techniques, some very verifiable criteria on the existence and exponential stability of anti-periodic solutions for the model are obtained. Our results are new and complementary to previously known results. An example is included to illustrate the feasibility and effectiveness of our main results.

Keywords: Cellular neural network, Anti-periodic solution, Exponentially stability, Time-varying delay, Impulse

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #17, pp. 140-149


Title of the Paper: A Novel Approach to Eliminating the Permutation and Scaling Indeterminacies of Block BSS

Authors: Wei Zhao, Yuehong Shen, Pengcheng Xu, Zhigang Yuan, Yimin Wei, Wei Jian

Abstract: This paper considers the permutation and scaling indeterminacy problem of blind source separation (BSS) in the case that the continuously mixing signals are split in time and processed block by block. When tying the separated signals in each time block, the recovered whole signals differ from the original sources up to permutation and scaling indeterminacies. Inspired by previous Permutation Method of reconstructing source signals in time domain, a novel approach is proposed to eliminate the inherent permutation and scaling indeterminacies when the block BSS is considered. This new method reformulates the mixing signals by overlapping adjacent signal blocks partially and utilizes the dependent correlation of the overlapping signals in each adjacent block to adjust the permutation and scaling parameters. Compared with the Permutation Method, this new method is more efficient in terms of separation quality and is much quicker in terms of execution speed. The performance of this novel approach is confirmed by computer simulations and realistic experiments performed on wireless communication system.

Keywords: blind source separation, independent component analysis, permutation and scaling indeterminacies, adjacent time blocks, overlapping signals, permutation method

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #16, pp. 131-139


Title of the Paper: A Subjective Method to Estimate the Voice Quality for Speech Watermarking Based on Improved Spread Spectrum Technique

Authors: Shervin Shokri, Mahamod Ismail, Nasharuddin Zainal

Abstract: This paper investigates the measure of voice quality for a digital speech watermarking scheme using a subjectivity method. Data rate, inaudibility, and robustness are considered more than voice quality in speech watermarking. Since any technique in speech telecommunication should have acceptable quality, the perceptual measurement of voice quality is seen as an important topic in audio and speech watermarking. The proposed scheme is simulated and then evaluated on the basis of the perceptual quality of received voice (speech) using mean opinion score (MOS) of 40 participants. Experimental results indicate that the average MOS at the receiver end is 2.75 out of 5. The results show that the perceptual audible quality of the proposed algorithm is between poor and fair.

Keywords: Improved spread spectrum, linear predictive (LP), MOS; BCH-code, speech watermarking

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #15, pp. 122-130


Title of the Paper: Robust Moving Object Detection Based on ViBe with Adaptive Shadow Detector

Authors: Zhihui Fan, Zhaoyang Lu, Jing Li, Chao Yao, Wei Jiang

Abstract: We propose the SAViBe+ algorithm, a new approach for moving object detection based on ViBe background subtraction algorithm with an adaptive shadow detector. Because ViBe cannot handle scenes containing gradual illumination variations, and eliminate shadows cast by moving objects, an adaptive shadow detector is designed to detect and eliminate the shadow of a moving object, adapting to variation of illumination in an automatic manner, which adopts texture and spatiotemporal information. This adaptive shadow detector is built with a texture model (TM) and a hue model (HM) to estimate the texture and intensity change of false foreground pixels respectively. A factor called Mean of Value (MofV) is proposed to work with HM to improve its efficiency. This algorithm is robust against false detection for different types of videos in indoor and outdoor scenes under various types of illumination taken by stationary cameras. Quantitative and qualitative performance evaluation carried out on the database of Change Detection Workshop(CDW’14) revealed that our scheme could operate in real-time, rapidly adapt to variation of illumination and environment online and outperform state-of-the-art methods.

Keywords: Object detection, Shadow removal, Adaptive shadow detector, Background subtraction, Motion detection, Surveillance

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #14, pp. 113-121


Title of the Paper: Research on the Optical Image Edge Detection Based on the Improved LOG Operator

Authors: Wang Yu, Wu Zhiqiang, Zhu Xinhua

Abstract: Edge detection has been a hot issue in image processing field for many years. This paper focuses on the LOG operator and its improvement methods. Firstly, a new edge detection template is proposed, which increases the detect direction for the original Laplace template and re-allocation of the weight reasonable. Secondly, this paper proposes an adaptive selection strategy of threshold for edge extraction based on the pixel neighborhood correlation. Experimental results show that the proposed algorithm significantly improved with better detection effect compared to traditional LOG operator and others, and very suitable for practical engineering.

Keywords: Image, Edge detection, LOG operator, Template, Threshold selection, Neighborhood correlation

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #13, pp. 107-112


Title of the Paper: Video Cut Detection Method Based on a 2D Luminance Histogram Using an Appropriate Threshold and a Post Processing

Authors: Youssef Bendraou, Fedwa Essannouni, Driss Aboutajdine, Ahmed Salam

Abstract: Segmenting a video is a fundamental component in video content based and automatic video analysis. Video cut detection is considered as a mainstay for video retrieval, especially for the keyframe extraction and the video summarization. In this paper, we present an algorithm for partitionning a video into shots. This algorithm abide to the two following steps. First, we calculate the difference in the luminance histogram between successive frames, which we compare against a predefined threshold to detect the cuts. A statistical study of the dissimilarity measures allows us to calculate that threshold in such a way that there are no missed shot. Second, we use a post processing to eliminate the false detections. Experimental results are presented to demonstrate the good performance of the proposed detector with high values of the evalution criteria.

Keywords: Video cut detection, Luminance Histogram, Post processing

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #12, pp. 99-106


Title of the Paper: Exposure Image Fusion of Enhancing Detail Visibility Based on Contrast Adjustment

Authors: Guo-Cheng Yang, Mei-Ling Li, Lei-Ting Chen, Hang Qiu

Abstract: To extract fine details from input bracketed images and preserve them in the final image, a novel exposure fusion method based on the nonsubsampled contourlet transform (NSCT) is presented in this paper?in which unique visual weight map is used for the detail extraction and an improved weight measurement is developed to remove the motion objects in dynamic scenes. Furthermore, a fast algorithm for contrast enhancement is applied to adjust the contrast of decomposition subbands and gain control is also introduced to modify the visibility of the blended subbands at different scales. Finally, the resulting image with more visible details is reconstructed by the inverse NSCT. Experimental results demonstrate that the proposed method can preserve fine details and produce sharper images, especially in enhancing detail visibility in the dark areas.

Keywords: Exposure fusion, NSCT, Weight map, Contrast enhancement, Gain control

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #11, pp. 88-98


Title of the Paper: Blind Identification of Underdetermined Mixtures Based on Charrelation Matrix

Authors: Zhongqiang Luo, Lidong Zhu

Abstract: In this paper, we propose a novel algorithm for underdetermined blind identification problems in blind signal separation. The proposed algorithm is based on the charrelation matrix of observations. The charrelation matrix can not only be considered as a generalized covariance matrix, but also incorporates higher-order information. It is significant for blind separation problem based on statistic characteristics to extract statistical information. The problem of underdetermined blind identification is converted as a tensor decomposition model. The mixing matrix is estimated from the rank-1 terms of the tensor decomposition. Theoretical analysis and simulation results illustrate that the proposed algorithm performs better estimated performance than the underdetermined blind identification algorithm based on second-order covariance and four-order cumulant respectively.

Keywords: blind identification, blind source separation, tensor decomposition

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #10, pp. 79-87


Title of the Paper: Negative Impedance Technique for Wide Dynamic Range in Radar Systems

Authors: Amir Almslmany, Qunsheng Cao, Caiyun Wang

Abstract: Radar receiver must be able to detect all targets that appears in the designed maximum range, these targets echo signals will have different power levels according to the radar cross section changing, the jamming, and the clutter, this paper proposes a new technique for increasing the wide dynamic range of the radar receiver in order to detect all the signals power levels, this technique based on using time varying gain amplifier (TVGA) for achieving compensation of the power loss due to range, and then using an adaptive sweep optimization (ASO) technique for increasing the linear rejoin of the time varying gain amplifier, the simulation was done using matlab, it shows that intermodulation ratio (IMR) was improved for the time varying gain amplifier electronic circuit, the comparison results with the old methods shows that the probability of detection for the radar was increased using the new technique (ASO/TVGA), for more validation the radar system was tested by detecting three targets at different ranges.

Keywords: Adaptive Sweep, Amplifier, Detection, Linearity, Time Varying

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #9, pp. 69-78


Title of the Paper: MUSIC Algorithm for RSSI-Based DoA Estimation on Standard IEEE 802.11/802.15.x Systems

Authors: Marco Passafiume, Stefano Maddio, Alessandro Cidronali, Gianfranco Manes

Abstract: Existing global positioning systems (GPS) applications are normally denied in indoor environments where, in spite of this limitation, a number of interesting applications are evolving into commercial products. At present, for indoor positioning, there are few cost-effective alternatives to GPS. One promising approach is based on the received signal strength indicator (RSSI) estimation, which is available in every IEEE standard compliant wireless transceiver, and includes useful information about the mutual positions between two position reference nodes. Extrapolating distance evaluation from RSSI is not reliable without the adoption of an accurate channel model [1],[2]. By using an anchor node/router with an array of directive antennas, it is possible to implement a spatial subdivision aimed at achieving an estimation of the direction of arrival (DoA) by evaluating the ratios between the single anchor’s antennas, and thus independently of the channel characteristics. This approach makes use of already existing spectral-based DoA localization algorithms ([3],[4]), but all of them assume a real-time analysis of both the amplitude and the phase of the received signals. In this article, we demonstrate analytically the capability of the MUSIC algorithm [3] to elaborate only the RSSI readings. We also compare the DoA localization performance using the classical information set (i.e., amplitude and phase) versus the use of the RSSI set (obtained simply by reading transceiver standard registers). In conclusion, we introduce some fundamental array design principles for optimal MUSIC RSSI implementation, with a real implementation tracking test.

Keywords: Indoor, positioning, tracking, WSN, DoA, RSSI, MUSIC, mobile devices, WiFi, Zigbee, Bluetooth

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #8, pp. 58-68


Title of the Paper: Low-Power OZGF Bank and MR Hamming Windowing for Embedded Speech Recognition

Authors: Brian Smith, John Sustersic, Michael Moore

Abstract: We present novel implementations of a One-Zero Gammatone Filter and a multiresolution Hamming Window with constant time complexity for low power digital implementation in embedded speech recognition systems. We compare our model with state-of-the-art basilar membrane models in terms of computational complexity and in terms of phone classification accuracy on the TIMIT dataset and show quantitative advantages in both, enabling better speech recognition for a broader class of power and resource constrained digital embedded systems.

Keywords: Gammatone Filterbank, Phone Recognition, Embedded Systems

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #7, pp. 52-57


Title of the Paper: A Novel Adaptive Object Tracking Method Based on Expected Likelihood Kernel

Authors: Hamd Ait Abdelali, Leila Essannouni, Fedwa Essannouni, Driss Aboutajdine

Abstract: Visual tracking is a new line of broad research. It is required for advanced vision-based applications such as visual surveillance and vision-based human-robot interaction. In this paper, we propose a new method of object detection and tracking algorithm using Adaptive Expected Likelihood Kernel. In this algorithm we combine between the probability product kernels as a similarity measure, and the integral image to increase the speed of the algorithm.

Keywords: Object tracking, Integral Image, Histogram-based, Expected Likelihood Kernel, Mean Shift

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #6, pp. 45-51


Title of the Paper: FPGA-Based Architectures for Image Processing Using High-Level Design

Authors: Yahia Said, Taoufik Saidani, Mohamed Atri

Abstract: This paper presents the design and implementation of image processing applications on field programmable gate array (FPGA). To improve the implementation time, Xilinx AccelDSP, a software for generating hardware description language (HDL) from a high-level MATLAB description has been used. Two FPGA-based architectures for image processing have been proposed: Color Space Conversion and Edge Detection. The designs were implemented on Spartan 3A DSP and Virtex 5 devices. Obtained results are discussed and compared with others architectures.

Keywords: HLS tools, design flow, Image processing, Xilinx AccelDSP, Matlab, FPGA

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #5, pp. 38-44


Title of the Paper: Design of Higher Order LP and HP Digital IIR Filter Using the Concept of Teaching-Learning Based Optimization

Authors: Damanpreet Singh, J. S. Dhillon

Abstract: In this article, Teaching-learning opposition based optimization (TLOBO) algorithm based on the natural phenomenon of teaching and learning is applied to design an optimal higher order stable low pass (LP) and high pass (HP) IIR digital filter using different design criterion. The original Teaching- Learning Based Optimization (TLBO) algorithm has been remodeled by merging the concept of opposition-based learning for selection of good candidates. In the first part of design process absolute magnitude response error is minimized. In second design phase, combination of four criterion is considered i.e. L1 -norm approximation of magnitude response, L2-norm approximation of magnitude response, ripples in pass band and stop band are minimized simultaneously by applying multiobjective optimization. The obtained design results of LP and HP, IIR filter are compared to other existing meta-heuristic algorithms. The simulation results reveal that the purposed TLOBO algorithm gives better performance in terms of convergence rate and quality of the filter.

Keywords: Digital infinite impulse response filters, Teaching-Learning-Based Optimization (TLBO), Magnitude response, Filter ripples, Multiobjective optimization

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #4, pp. 29-37


Title of the Paper: Equivalence Between SLNR and MMSE Precoding Schemes in the K-User MISO Interference Channel

Authors: Bangwon Seo, Joonwoo Shin

Abstract: We consider a transmit precoder design for the K-user multiple-input single-output (MISO) interference channel in which each transmitter is equipped with multiple transmit antennas and each receiver employs a single receive antenna. First, we derive a closed-form expression for a minimum mean-square error (MMSE) precoder and an alternative expression for a signal-to-leakage plus noise ratio (SLNR) precoder. Then, the equivalence between the two precoders is proved. Through simulation results, we demonstrate that the sum capacity and bit error rate (BER) performance of the SLNR precoder are the same as the MMSE precoder and that they are better than that of the zero-forcing (ZF) precoder.

Keywords: Interference channel, multiple-input single-output, precoding, minimum mean squared error (MMSE), signal-to-leakage-plus noise ratio (SLNR)

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #3, pp. 23-28


Title of the Paper: A Robust System for Printed and Handwritten Character Recognition of Images Obtained by Camera Phone

Authors: H. El Bahi, Z. Mahani, A. Zatni, S. Saoud

Abstract: In Recent years, character recognition has gained more importance in the area of pattern recognition owning to its application in various domains. The biggest challenge is to build an efficient optical character recognition system (OCR) able to recognize documents, also to allow overcoming the problems of blurred and noisy image. Many OCRs systems are been applied, but less interest have been given to document images obtained by camera phone. In this paper, we will present a complete offline handwritten and machine-printed character recognition system for isolated character acquired via camera-mobile. Our system includes five stages namely: preprocessing, segmentation, feature extraction and classification. We investigated various techniques in the preprocessing stage in order to select the best. In feature extraction and classification stages, we examined several features methods with three different types of classifiers The Support vector machines (SVM), The Na?ve Bayes (NB) and the Multilayer Perceptron (MLP). We performed the experiments with two databases of handwritten and machine-printed character images. The results indicate that the proposed system is very effective and yields good recognition rate for character images obtained by camera phone.

Keywords: Preprocessing, Feature Extraction, Classification, OCR, SVM, MLP

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #2, pp. 9-22


Title of the Paper: An Approach to Interesting Objects Detection in Low Quality Image Sequences for Fisheries Management

Authors: Zuojin Li, Liukui Chen, Jun Peng, Lei Song

Abstract: In order to extract interest objects in low quality image sequences from fisheries management, this paper proposes a new significant feature extraction method based on cascade framework. This algorithm involves preprocessing image sequences, clipping interesting areas, extracting SURF features, removing boundary features, and acquiring significant features with interesting objects. We apply our algorithm to fisheries management for counting and matching ships and cars, the proposed method can efficiently detect multiple objects from real-scene video frames with averaged accuracy 91.63%.

Keywords: SURF Features, Interest Objects, Features Extraction, Multiple Objects Detection, Low Quality Image Processing

WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #1, pp. 1-8


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