WSEAS CONFERENCES. WSEAS, Unifying the Science

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 Volume 5, 2009
Print ISSN: 1790-5052
E-ISSN: 2224-3488








Issue 1, Volume 5, January 2009

Title of the Paper:  Simple and Powerful Instrument Model for the Source Separation of Polyphonic Music


Authors: Kristof Aczel, Istvan Vajk

Abstract: This article presents a new approach to sound source separation. The introduced algorithm is based on spectral modeling of real instruments. The separation of independent sources is carried out by dividing the energy of the mixture signal based on these instrument models. This way it is possible to regain some of the information that was lost when the independent sources were mixed together into a single signal. The paper presents the theory behind the proposed separation system, then focuses on the instrument model that is the basic element of the approach. Measurement results are given for polyphony levels from 2 to 10 demonstrating the separation quality, with special regard to the effect of prints on the result.

Keywords: Sound separation, instrument print, polyphonic music, energy split

Title of the Paper:  An Overview of Different Wideband Direction of Arrival(DOA) Estimation Methods


Authors: Sandeep Santosh, O. P. Sahu, Monika Aggarwal

Abstract: The Direction of Arrival (DOA) estimation methods are useful in Sonar, Radar and Advanced Satellite and Cellular Communication systems. In this paper different Direction of Arrival(DOA) methods such as Coherent Signal Subspace Processing (CSSM), the Weighted Average of Signal Subspaces (WAVES) and Test of Orthogonality of Projected Subspaces (TOPS) and Incoherent MUSIC(IMUSIC) is presented and their performance is also compared . The TOPS method performs better than others in mid signal–to-noise ratio (SNR) ranges, while CSSM and WAVES work better in low SNR. Incoherent methods like IMUSIC works best at high SNR.

Keywords: Direction of Arrival, CSSM, WAVES, TOPS,IMUSIC, SNR

Title of the Paper:  Fast Algorithms with Low Complexity for Adaptive Filtering


Authors: Madjid Arezki, Daoud Berkani

Abstract: The numerically stable version of fast recursive least squares (NS-FRLS) algorithms represent a very important load of calculation that needs to be reduced. Its computational complexity is of 8L operations per sample, where L is the finite impulse response filter length. We propose an algorithm for adaptive filtering, while maintaining equilibrium between its reduced computational complexity and its adaptive performances. We present a new (M-SMFTF) algorithm for adaptive filtering with fast convergence and low complexity. It is the result of a simplified FTF type algorithm, where the adaptation gain is obtained only from the forward prediction variables and using a new recursive method to compute the likelihood variable. This algorithm presents a certain interest, for the adaptation of very long filters, like those used in the problems of echo acoustic cancellation, due to its reduced complexity, its numerical stability and its convergence in the presence of the speech signal. Its computational complexity is of 6L and this is considerably reduced to 2L+4P when we use a reduced P-size (P<<L) forward predictor.

Keywords: Adaptive Filters, FIR model, Fast Algorithms, Stability, Convergence Speed, Tracking capability

Title of the Paper:  Signal Processing's Importance in Manufacturing of a Special Device


Authors: Mihaiela Iliescu, Brindus Comanescu, Emil Nutu

Abstract: Lot of the parts manufactured for various required purposes involve machining processes, such as turning, drilling or, cold pressing processes, such as stamping, drawing, extruding, etc. When these processes are involved, special attention should be given to their specific force values and, as consequence, to devices used in measuring force’s values. The most important element of a force measuring device is represented by elastic element and, further, by the transducers “fitted” to it. Appropriate transducers signal processing is essential when device’s characteristics have to de specified and, more, to be tested and applied into real manufacturing conditions.

Keywords: Elastic element, resistive transducer, device, process force, calibrating, data acquisition

Title of the Paper:  An Optimal Robust Digital Image Watermarking based on Genetic Algorithms in Multiwavelet Domain


Authors: Prayoth Kumsawat, Kitti Attakitmongcol, Arthit Srikaew

Abstract: In this paper, we propose digital image watermarking algorithm in the multiwavelet transform domain. The embedding technique is based on the quantization index modulation technique and this technique does not require the original image in the watermark extraction. We have developed an optimization technique using the genetic algorithms to search for optimal quantization steps to improve the quality of watermarked image and robustness of the watermark. In addition, we analyze the performance of the proposed algorithm in terms of peak signal to noise ratio and normalized correlation. The experimental results show that our proposed method can improve the quality of the watermarked image and give more robustness of the watermark as compared to previous works.

Keywords: Image watermarking; Multiwavelet; Multiwavelet tree; GA; Quantization index modulation

Issue 2, Volume 5, February 2009

Title of the Paper:  Wavelet Filter Design based on the Lifting Scheme and its Application in Lossless Image Compression


Authors: Tilo Strutz

Abstract: The description of filter banks using lifting structures does not only benefit low-complexity implementation in software or hardware, but is also advantageous for the design of filter banks because of the guaranteed perfect reconstruction property. This paper proposes a new design method for wavelet filter banks, which is explained based on a single lifting structure suitable for 9/7 filter pairs. The filters are derived directly, the factorisation of known filters is not necessary. In addition, it is shown that the signal boundaries can be treated with little computational efforts. The modification of the standard design constraints leads to families of related filter pairs with varying characteristics. It includes a filter bank that can be implemented in integer arithmetic without divisions, shows better performance than the standard 9/7 filter bank for lossless image compression and competitive performance when applied in lossy compression.

Keywords: Lifting scheme, Filter design, Wavelet transform, Image coding

Title of the Paper:  Image Restoration via Wiener Filtering in the Frequency Domain


Authors: Hiroko Furuya, Shintaro Eda, Testuya Shimamura

Abstract: In this paper, first, the performance of the Wiener filter in the frequency domain for image restoration is compared with that in the space domain on images degraded by white noise. After finding that the Wiener filter in the frequency domain is more effective than that in the space domain in an ideal case, power spectrum estimation methods for the Wiener filter in the frequency domain are discussed. Three approaches are considered; frequency band division processing (FBDP), modified FBDP and averaging high frequency components (AHFC). The performances of the Wiener filter with the three approaches for power spectrum estimation are investigated through computer simulation experiments. It is shown that the frequency domain Wiener with the modified FBDP provides a superior performance relative to that with the FBDP and AHFC.

Keywords: Image restoration, White noise, Power spectrum estimation, Wiener filter, Frequency domain

Title of the Paper:  A Novel Watermarking Scheme for JPEG Images


Authors: Vikas Saxena, J. P. Gupta

Abstract: Image watermarking with both insensible detection and high robustness capabilities is still a challenging problem. Even if some of the watermarking areas involve huge financial implication, there are relatively fewer efforts presented, which primarily focus the sustainability against some attacks, which are specific to financial application area particularly. One of such application area is “Fingerprinting” and a major threat for this area is “Collusion Attack”. This paper presents an inherently collusion attack resistant (ICAR) scheme for hiding a logo-based watermark in JPEG images. This scheme is based on averaging of low and middle frequency coefficients of block Discrete Cosine Transform (DCT) coefficients of an image. Experimental results show the robustness of the proposed scheme against the JPEG compression and other common image manipulations.

Keywords: Collusion attack, Discrete Cosine Transform (DCT), Image watermarking, JPEG compression

Title of the Paper:  Effect of Geoacoustic Parameters Uncertainties on Acoustic Transmission Loss Prediction


Authors: Wei Gao

Abstract: Geoacoustic parameters inverted from reverberation vertical correlation (RVC) are often directly used to predict the acoustic transmission loss (ATL) in shallow water. However, little work has been applied to the problem of quantifying uncertainty in predicted ATL produced by geoacoustic parameters uncertainties. In this paper, a posterior predictive probability analysis method (PPPAM) is first employed to evaluate the effects of geoacoustic parameters uncertainties inverted from RVC data on both coherent and incoherent ATL predictions. Where, the geoacoustic parameters uncertainties are characterized by their posterior probability distributions (PPD). And then the uncertainties of ATL prediction are analyzed quantitatively based on the posterior predictive probability distributions of ATL, which are the function of the PPDs of geoacoustic parameters and can be estimated using a Markov Chain Monte Carlo sampling method. Finally, the Yellow Sea Reverberation experimental results illustrate the PPPAM and show that: (1) in the range from 1km to 5 km, the mean values of 90% posterior credibility intervals (PCI) of coherent and incoherent ATL in frequency range of 500~800Hz exceed 6dB and 3dB, respectively; (2) the coherent ATL are more difficult to predict near the positions of destructive interference of the normal modes. These results derived in this paper are helpful to evaluate and improve the detection and localization performance of sonar system.

Keywords: Transmission loss prediction, Uncertainty analysis, Geoacoustic inversion, Posterior predictive probability, Reverberation vertical correlation.

Issue 3, Volume 5, March 2009

Title of the Paper:  Eight-Phase Sequence Sets Design for Radar


Authors: S. P. Singh, S. A. Muzeer, K. Subba Rao

Abstract: In this paper a novel Modified Simulated Annealing Algorithm (MSAA) is used as global optimization technique to find the solution of combinatorial optimization problem which is usually difficult to tackle. MSAA combines good methodologies like global minimum converging property of Simulated Annealing algorithm and fast convergence rate of Hamming scan algorithm. Orthogonal Netted Radar System (ONRS) and spread spectrum communication system can fundamentally improve the system performance by using a group of specially designed orthogonal signals. MSAA is used to synthesize orthogonal eight-phase sequence sets with good autocorrelation and cross correlation properties. Some of the synthesized sequence sets are presented, and their properties are better than four-phase sequence sets known in the literature. The synthesized eight-phase sequence sets are promising for practical application to Netted Radar System and spread spectrum communication. The effect of Doppler shift on synthesized sequences set is also investigated using ambiguity function. The convergence rate of the algorithm is shown to be good.

Keywords: Hamming Scan, Netted Radar, Polyphase code, Radar signal design, Simulated annealing

Title of the Paper:  Biologically Inspired Evolutionary Computing tools for the Extraction of Fetal ElectroCardioGram


Authors: Ravi Kumar Jatoth, Saladi S. V. K. K. Anoop, Ch. Midhun Prabhu

Abstract: Signals recorded from the human body provide valuable information about the biological activities of body organs. The spectral properties of different organs help in medical diagnosis. Even small changes in functioning of organs is indicated by the changes in their spectra. Fetal heart rate extraction from the abdominal ECG is of great importance because the information carried by it is helpful in assessing appropriately the fetus well-being during pregnancy. Fetal ECG is always contaminated by a drift and interference caused by several bioelectric phenomena, or by various types of noise, such as intrinsic noise from the recorder and noise from electrode-skin contact. The low Signal to noise Ratio of fetal ECG makes it difficult to analyze it effectively. Accurate detection of QRS complex is a pre-requisite in the assessment of fetal heart beat.In this paper we utilize an intelligent Adaptive Filter for noise cancellation in the effective extraction and analysis of fetal ECG. The PSO based adaptive noise cancellation technique is shown to be superior to the conventional FIR adaptive filtering.

Keywords: Fetal ECG, Adaptive Noise Cancellation, Least Mean Squares(LMS) ,Genetic Algorithm (GA), Particle Swarm Optimization (PSO)

Title of the Paper:  A Comparison of Neural Networks for Real-Time Emotion Recognition from Speech Signals


Authors: Mehmet S. Unluturk, Kaya Oguz, Coskun Atay

Abstract: Speech and emotion recognition improve the quality of human computer interaction and allow easier to use interfaces for every level of user in software applications. In this study, we have developed two different neural networks called emotion recognition neural network (ERNN) and Gram-Charlier emotion recognition neural network (GERNN) to classify the voice signals for emotion recognition. The ERNN has 128 input nodes, 20 hidden neurons, and three summing output nodes. A set of 97920 training sets is used to train the ERNN. A new set of 24480 testing sets is utilized to test the ERNN performance. The samples tested for voice recognition are acquired from the movies “Anger Management” and “Pick of Destiny”. ERNN achieves an average recognition performance of 100%. This high level of recognition suggests that the ERNN is a promising method for emotion recognition in computer applications. Furthermore, the GERNN has four input nodes, 20 hidden neurons, and three output nodes. The GERNN achieves an average recognition performance of 33%. This shows us that we cannot use Gram-Charlier coefficients to discriminate emotion signals. In addition, Hinton diagrams were utilized to display the optimality of ERNN weights.

Keywords: Back propagation learning algorithm, Neural network, Emotion, Speech, Power Spectrum, Fast-Fourier Transform (FFT), Bayes optimal decision rule.

Title of the Paper:  Experiments in Room Acoustics: Modelling of a Church Sound Field and Reverberation Time Measurements


Authors: J. Quartieri, S. D'Ambrosio, C. Guarnaccia, G. Iannone

Abstract: In this paper a study of the acoustical response of a new built church is shown. This study is based on the measurement of reverberation time, adopting the noise interrupted method, according to the International Standard. This method allows to evaluate the reverberation time by means of acoustical sound level acquisition and analysis. The reverberation time is one of the principal parameters to be optimized in order to design and/or verify the acoustical behaviour of a room and consequently to guarantee a good people hearing sensation. In a post-opera intervention, the reverberation time can be improved modifying the reflecting surfaces of walls, floor and roof, in order to reduce the energetic contributions of late reflections. This improvement can be achieved by replacing or covering reflecting surfaces with absorbing panels or carpets. The design of an appropriate intervention can be aided by a dedicated simulation software, as it is shown in the last part of the paper.

Keywords: Acoustical Field, Church Acoustics, Reverberation Time, Simulation Software

Issue 4, Volume 5, April 2009

Title of the Paper:  Range Migration Compensation Based on Range-Direction Coupling in SFDLFM MIMO Radar


Authors: Li Jun, Liu Hongming, He Zishu, Cheng Ting

Abstract: Wide low-gain transmitting beam and long time integration are adopted in the orthogonal signal MIMO radar to survey the interested area. The range migration of moving target is a pivotal problem faced in the MIMO radar. Orthogonal LFM signal is one of the most familiar waveforms in MIMO radar, and this paper discusses the range migration compensation problem in the MIMO radar using Stepped Frequency Division Linear Frequency Modulation (SFDLFM) signal. A new compensation method based on the proper rangedirection coupling relationship is put forward. It can achieve a good compensation effect with low computation complexity. Theoretical deduction and simulation results demonstrate the validity of this method.

Keywords: MIMO radar, range migration, coherent integration, motion compensation, SFDLFM signal, range-direction coupling

Title of the Paper:  OTHR Impulsive Interference Detection based on AR Model in Phase Domain


Authors: Tao Liu, Jie Wang

Abstract: Based on autoregression(AR) model in phase domain, this paper proposes a novel impulsive interference(IMI) detection algorithm for over-the-horizon radar. This is achieved by regarding IMI phase spectrum as complex sinusoid signal and modeling it by AR model. Then we can take the full advantage of the sinusoid signal estimation algorithm. After getting zeros of AR model transfer function, the amount of the contained sinusoid signals and their frequency parameters can be estimated. The angular value of zero is exactly corresponding to IMI position of interest. Details and improvements are also discussed in this paper. This algorithm's operational performance is evaluated using experimental data sets collected from a high frequency surface wave (HFSW) OTHR system, and is proved to be suitable for most types of IMIs.

Keywords: Based on autoregression(AR) model in phase domain, this paper proposes a novel impulsive interference(IMI) detection algorithm for over-the-horizon radar. This is achieved by regarding IMI phase spectrum as complex sinusoid signal and modeling it by AR model. Then we can take the full advantage of the sinusoid signal estimation algorithm. After getting zeros of AR model transfer function, the amount of the contained sinusoid signals and their frequency parameters can be estimated. The angular value of zero is exactly corresponding to IMI position of interest. Details and improvements are also discussed in this paper. This algorithm's operational performance is evaluated using experimental data sets collected from a high frequency surface wave (HFSW) OTHR system, and is proved to be suitable for most types of IMIs.

Title of the Paper:  Fast Image Matching on Web Pages


Authors: Hazem M. El-Bakry, Nikos Mastorakis

Abstract: In this paper, a fast method for image matching on web pages is presented. Such method relies on performing cross correlation in the frequency domain between the web image and the image given in the user query. The cross correlation operation is modified. Instead of performing dot multiplication in the frequency domain, image subtraction is applied in two dimensions. It is proved mathematically that the number of computation steps required for the proposed fast matching method is less than that needed by conventional matching.

Keywords: Fast image subtraction, frequency domain, cross correlation, image matching

Issue 5, Volume 5, May 2009

Title of the Paper:  The Use of Wavelets in Speaker Feature Tracking Identification System Using Neural Network


Authors: Wael Al-Sawalmeh, Khaled Daqrouq, Abdel-Rahman Al-Qawasmi, Tareq Abu Hilal

Abstract: Continuous and Discrete Wavelet Transform (WT) are used to create text-dependent robust to noise speaker recognition system. In this paper we investigate the accuracy of identification the speaker identity in non- stationary signals. Three methods are used to extract the essential speaker features based on Continuous, Discrete Wavelet Transform and Power Spectrum Density (PSD). To have better identification rate, two types of Neural Networks (NNT) are studied: The first is Feed Forward Back Propagation Neural Network (FFBNN) and the second is perceptron. Up to 98.44% identification rate is achieved. The presented system depends on the multi-stage features extracting due to its better accuracy. The multistage features tracking based system shows good capability of features tracking for tested signals with SNR equals to -9 dB using Wavelet Transform, which is suitable for non-stationary signal.

Keywords: Speaker identification; Continuous and discrete wavelet transform; Linear prediction coefficient; and text-dependent

Title of the Paper:  Noisy Image Restoration Based on Boundary Resetting BDND and Median Filtering with Smallest Window


Authors: Cheng-Hsiung Hsieh, Po-Chin Huang, Sheng-Yung Hung

Abstract: In this paper, a restoration approach for noisy image is proposed where a boundary resetting boundary discriminative noise detection (BRBDND) and a median filtering with smallest window (MFSW) are applied. In the proposed image restoration approach, two stages are involved: noise detection and noise replacement. The BRBDND is used to detect noisy pixels in an image. If a pixel is uncorrupted, then keep it intact. Or replace it with an uncorrupted neighborhood pixel through the MFSW. Note that miss detection happens in the BDND presented in [17] when the noise density is high. The miss detection is even worse for cases with unbalanced noisy density where the portions for the salt noise and the pepper noise are different. A boundary resetting scheme is incorporated into the BDND. By this doing, the problem of miss detection described above can be prevented. Note that a larger window used in the median filtering leads to a stronger smoothing effect on the restored image. The reported median filtering approaches, like the modified noise adaptive soft-switching median filter (MNASM) in [17], uses larger windows generally. Thus, a median filtering with smallest window (MFSW) is proposed to improve the visual quality of restored image. Two examples are provided to justify the proposed image restoration approach BRBDND/MFSW where comparisons are made with the BDND/MNASM. The results indicate that the proposed BRBDND is able to deal with the miss detection problem in the BDND. It also shows that the proposed MFSW indeed improves the visual quality of restored image as expected. The simulation results suggest that the proposed restoration approach BRBDND/MFSW generally outperforms the BDND/MNASM both in the PSNR and the visual quality of restored image.

Keywords: Noise removal, noise detection, median filtering, BDND, image restoration

Title of the Paper:  Fast Copy-Move Forgery Detection


Authors: Hwei-Jen Lin, Chun-Wei Wang, Yang-Ta Kao

Abstract: This paper proposes a method for detecting copy-move forgery over images tampered by copy-move. To detect such forgeries, the given image is divided into overlapping blocks of equal size, feature for each block is then extracted and represented as a vector, all the extracted feature vectors are then sorted using the radix sort. The difference (shift vector) of the positions of every pair of adjacent feature vectors in the sorting list is computed. The accumulated number of each of the shift vectors is evaluated. A large accumulated number is considered as possible presence of a duplicated region, and thus all the feature vectors corresponding to the shift vectors with large accumulated numbers are detected, whose corresponding blocks are then marked to form a tentative detected result. Finally, the medium filtering and connected component analysis are performed on the tentative detected result to obtain the final result. Compared with other methods, employing the radix sort makes the detection much more efficient without degradation of detection quality.

Keywords: Forgery Detection, Copy-move Forgery, Singular Value Decomposition (SVD), Principal Component Analysis (PCA), Lexicographical Sort, Scale Invariant Feature Transform (SIFT) Descriptors, Log-polar Coordinates, Radix Sort, Connected Component Analysis

Title of the Paper:  Color Video Segmentation using Fuzzy C-Mean Clustering with Spatial Information


Authors: M. Arfan Jaffar, Bilal Ahmed, Nawazish Naveed, Ayyaz Hussain, Anwar M. Mirza

Abstract: Video segmentation can be considered as a clustering process that classifies one video succession into several objects. Spatial information enhances the quality of clustering which is not utilized in the conventional FCM. Normally fuzzy c-mean (FCM) algorithm is not used for color video segmentation and it is not robust against noise. In this paper, we presented a modified version of fuzzy c-means (FCM) algorithm that incorporates spatial information into the membership function for clustering of color videos. We used HSV model for decomposition of color video and then FCM is applied separately on each component of HSV model. For optimal clustering, grayscale image is used. Additionally, spatial information is incorporated in each model separately. The spatial function is the summation of the membership function in the neighborhood of each pixel under consideration. The advantages of this new method are: (a) it yields regions more homogeneous than those of other methods for color videos; (b) it reduces the spurious blobs; and (c) it removes noisy spots. It is less sensitive to noise as compared with other techniques. This technique is a powerful method for noisy color video segmentation and works for both single and multiple-feature data with spatial information.

Keywords: Color video segmentation, spatial fuzzy c-mean, and cluster validity, Frame change detection

Issue 6, Volume 5, June 2009

Title of the Paper:  Real-Time Detection of Face and Iris


Authors: Chai Tong Yuen, Mohamed Rizon, Muhammad Shazri

Abstract: In this study, a computational algorithm has been developed to automatically detect human face and irises from color images captured by real-time camera. Haar cascade-based algorithm has been applied for simple and fast face detection. The face image is then converted into grayscale image. Three types of image processing techniques have been tested respectively to study its effect on the performance of iris detection algorithm. Then, iris candidates are extracted from the valley created at the face region. The iris candidates are paired up and the cost of each possible pairing is computed by a combination of mathematical models. Finally, the positions of the detected irises are used as a reference to refine the face region. The algorithm has been tested by quality images from Logitech camera and noisy images from Voxx CCD camera. The proposed algorithm has achieved 83.60% as the highest success rate of iris detection under a user-friendly and unconstraint office environment.

Keywords: Face detection, Iris detection, Illumination normalization, Face recognition

Title of the Paper:  GSM/GPRS Signal Strength Measurements in Aircraft Flights under 3,000 Meters of Altitude


Authors: Juan Antonio Romo, Gerardo Aranguren, Javier Bilbao, Inigo Odriozola, Javier Gomez, Luis Serrano

Abstract: Nowadays an increasing demand to use mobile telephones devices in aircraft flights is being acknowledged, both in commercial and in aviation general flights. 2G and 3G mobile communications networks have a great penetration in terrestrial surface of populated areas. Nevertheless land mobile networks have not been planned to operate within the air space. The main objective of this project has been to collect GSM/GPRS signal level measurement samples in the air space used by general aviation, transmitted by terrestrial base stations. Subsequently the values of obtained signal have been analyzed in order to extract conclusions on the applicability of the current mobile terrestrial communications on board of aircraft in general aviation.

Keywords: GSM, GPRS, measurement, base station antennas, data acquisition, aeronautics, data visualization

Title of the Paper:  A Simple Algorithm for Automated Skin Lesion Border Detection


Authors: P. Tzekis, A. Papastergiou, A. Hatzigaidas, Z. Zaharis, D. Kampitaki, P. Lazaridis, M. Goula

Abstract: Prompt diagnosis is the most reliable solution for an effective treatment of melanoma. There is an ongoing research for providing computer-aided imaging tools in order to support the early detection and diagnosis of malignant melanomas. The first step towards producing such a diagnosis system is the automated and accurate boundary detection of skin lesion. Therefore, the present study introduces a new, simple, and very fast algorithm that has the ability to detect effectively and automatically the border of potential melanoma. The complexity of the proposed algorithm is O( N ), and thus the execution time, is dramatically minimized.

Keywords: Melanoma, Dermatoscopy, ABCD rule, Image, processing, Border detection

Issue 7, Volume 5, July 2009

Title of the Paper:  Perceptual Distortion Metric for Stereo Video Quality Evaluation


Authors: Zhongjie Zhu, Yuer Wang

Abstract: Stereo video is regarded as an important developing trend of video technology and there is an increasing need to develop efficient and perceptually consistent methods for stereo video quality evaluation in the fields of stereo video signal processing. In this paper, a perceptual metric for stereo video quality evaluation is proposed based on the state-of-the-art physiological and psychological achievements on human visual system (HVS). Several main HVS properties related to stereo video are analyzed and a multi-channel vision model based on 3D wavelet decomposition is proposed. Simulations are performed and experimental results reveal that, compared with the traditional objective metrics such as peak signal-to-noise ratio (PSNR) and mean squared error (MSE), the proposed metric is more perceptually consistent.

Keywords: Human visual system, stereo video, image quality evaluation, 3D wavelet decomposition

Title of the Paper:  A Wideband Digital Beamforming Method Based on Stretch Processing


Authors: Huiyong Li, Xuhong Zhang, Zishu He, Jia Yu

Abstract: The calculation of wideband digital beamforming using traditonal methods is so large that it is hard to realize in project. This paper describes a wideband digital beamforming method on the base of stretch processing for linear frequency modulated (LFM) waveforms. This method offers advantages that are moderate data rate for wideband signal processing by reducing the signal bandwidth greatly. In addition, the method not only can get high range resolution of wideband array radar, but also can form good shape pattern with null at interference, as the simulation results show. To the most important, this method compared to traditional methods is easier for engineering implementation greatly.

Keywords: Digital beamforming (DBF), linear frequency modulated (LFM), Stretch Processing , wideband, Digital array radar

Title of the Paper:  Fast Word Detection in a Speech Using New High Speed Time Delay Neural Networks


Authors: Hazem M. El-Bakry, Nikos Mastorakis

Abstract: This paper presents a new approach to speed up the operation of time delay neural networks for fast detecting a word in a speech. The entire data are collected together in a long vector and then tested as a one input pattern. The proposed fast time delay neural networks (FTDNNs) use cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented time delay neural networks is less than that needed by conventional time delay neural networks (CTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Fast Time Delay Neural Networks, Cross Correlation, Frequency Domain, Word Detection in a speech

Title of the Paper:  An Efficient QR-based Selection Criterion for Selecting an Optimal Precoding Matrix Employed in a Simplistic MIMO Detection


Authors: Chien-Hung Pan

Abstract: In multiple-input multiple-output (MIMO) channel (H) communication, when channel status information (CSI) is known to the receiver but not to the transmitter, the precoding technique can achieve a highly reliable communication link, when the receiver informs an optimal precoding matrix index to the transmitter based on current CSI. To select an optimal precoding matrix (F), the maximum capacity selection criterion and the maximum minimum singular value selection criterion are developed. However, with QR-decomposition detection (HF = QR) in the precoding system, these two selection criteria may involve high complexity and poor detection performance due to the full matrix multiplication and inaccurate detection of the first layer, respectively. In this paper, to simplify the QR-decomposition processes, the real and imaginary parts of channel elements are rearranged to achieve a column-wise orthogonal structure to reduce the repeated computation. In precoding systems, to achieve 1) low-complexity and 2) performance enhancement, the efficient QR-based selection (QR-selection) criterion is proposed to select an optimal precoding matrix by maximizing the absolute value of the lowest layer of the upper triangular matrix R. For low-complexity, to reduce the multiplication complexity of computing R, we prove that the absolute value of R is equal to the absolute value of ( ), where . Based on this equivalence, we can reduce the multiplication complexity because the number of multiplications for computing RF is less than the number of multiplications for computing HF. For performance enhancement, the proposed QR-selection criterion can effectively mitigate the impact of error-propagation because the probability of an early error in the sequence of decisions is lower. Simulation results show that the proposed scheme with a low-complexity level has a better performance than others, and that it can improve detection performance as the codebook size increases.

Keywords: Multiple-input multiple-output, precoding, QR-decomposition, capacity selection, minimum singular value selection, QR selection, column-wise orthogonal structure, codebook

Issue 8, Volume 5, August 2009

Title of the Paper: Methods of Measure and Analyse of Video Quality of the Image


Authors: Iulian Udroiu, Ioan Tache, Nicoleta Angelescu, Ion Caciula

Abstract: This paper present an analysis of the method for the evaluation of quality of the images from the video signal. The results are based on the simulation of the human perception. The device used for the evaluation is a TEKTRONIX PQA500 Picture Quality Analyzer.

Keywords: Image quality, video quality, PQR, DMOS, PSNR

Title of the Paper: Reconfigurable Architecture of Systolic Array Processors for Real Time Remote Sensing Image Enhancement/Reconstruction


Authors: A. Castillo Atoche, D. Torres Roman, Y. Shkvarko

Abstract: In this paper, we propose a reconfigurable architecture of systolic array (SA) processors for near real time implementation of high-resolution reconstruction of remote sensing (RS) imagery. The proposed design is based on a Field Programmable Gate Array and performs the image enhancement/reconstruction tasks in an efficient reconfigurable processing architecture mode that involves the systolic array processors aimed to meet the (near) real time imaging systems requirements in spite of conventional computations. In particular, the reconfigurable architecture of SA processors is employed with the objective to decrease the computational load of the large-scale RS image enhancement/reconstruction tasks required to implement the RS enhancement/reconstruction algorithms based on the descriptive regularization techniques with the corresponding iterative fixed-point Projection Onto Convex Sets unified via the proposed Hardware/Software Co-Design paradigm.

Keywords: Remote sensing, Reconfigurable architecture, FPGA, Systolic array processors, Hardware/Software co-design

Title of the Paper: A Fuzzy Qualitative Framework for Indoor Rowing Kinematics Analysis


Authors: Ante Panjkota, Ivo Stancic, Tamara Supuk

Abstract: In this article an outline of a fuzzy qualitative framework for the indoor rowing kinematics analysis have been proposed. Main goal of introducing this fuzzy qualitative framework is to bridge the gap between high level of quantitative details obtained with various present – day sensory or video inputs and symbolic representation used by rowing experts. A Fuzzy qualification process of kinematic parameters is done on the basis of previously collected quantitative data and with possession of prior contextual knowledge for their qualification by rowing experts. Quantitative data acquisition is included indoor rowing kinematics recording by video motion tracking system. Generalizations of the proposed method on kinematics analysis of a common indoor human motion, problems of symbolic representation, as well as guidelines for method improvement are briefly discussed.

Keywords: Fuzzy qualitative analysis, indoor rowing, quantitative analysis, fuzzification, human motion

Issue 9, Volume 5, September 2009

Title of the Paper: Non-Linear Image Representation Based on IDP with NN


Authors: Roumen Kountchev, Stuart Rubin, Mariofanna Milanova, Vladimir Todorov, Roumiana Kountcheva

Abstract: In this paper is offered a method for non-linear still image representation based on pyramidal decomposition with a neural network. This approach is developed by analogy with the hypothesis for the way humans do image recognition using consecutive approximations with increasing similarity. A hierarchical decomposition, named Inverse Difference Pyramid (IDP), is used for the image representation. The approximations in the consecutive decomposition layers are represented by the neurons in the hidden layers of the neural networks (NN). This approach ensures efficient description of the processed images and as a result – a high compression ratio. This new way for image representation is suitable for various applications (efficient compression, multi-layer search in image databases, etc.).

Keywords: Non-linear image representation, pyramidal decomposition, neural networks

Title of the Paper: Multi-view Object Representation with Modified 2-Layer IDP Decomposition


Authors: Roumen Kountchev, Vladimir Todorov, Roumiana Kountcheva

Abstract: In the paper is presented one new method for multi-view object representation based on image decomposition with modified Inverse Difference Pyramid. The method offers new approach for efficient description of the multi-view images using one of them as a reference one. The decomposition has a relatively low computational complexity because it is based on orthogonal transforms (Walsh-Hadamard, DCT, etc.). The relations which exist between transform coefficients from the consecutive decomposition layers permit significant reduction of the coefficients needed for the high-quality object representation.

Keywords: Fuzzy qualitative analysis, indoor rowing, quantitative analysis, fuzzification, human motion

Issue 10, Volume 5, October 2009

Title of the Paper: A New Method of DOA Estimation for Uniform Antenna Array


Authors: Ling Qin, Huiyong Li, Jia Yu, Zishu He

Abstract: A novel method of direction-of-arrival (DOA) estimation based on subarray beamforming for uniform circular arrays is proposed. In this method, the beamform manifold of uniform circular arrays is transformed via virtual structure, and then the virtual array is divided into two subarrrays. The target DOA is estimated from the phase shift between the reference signal and its phase-shifted version by subarray beamforming. Since the reference signal is obtained after interference rejection, the effect of interference The computation of the proposed method is simple, and the number of the signal sources of target is not bounded by the number of antenna elements. Simulation results demonstrate that proposed method has significantly improved estimation resolution, capacity, and accuracy relative to other method.

Keywords: Direction of arrival (DOA), estimation, virtual array, subarray beamforming

Title of the Paper: An Improved and Fast Approach to Parameter Estimation of SFM Signal Using Carson's Rule


Authors: Xuejun Sun, Bin Tang

Abstract: Fast parameter estimation of sinusoidal frequency modulation signal (SFM) in additive white Gaussian noise is considered. A technique based on Carson's rule is developed to estimate the frequency modulation index; the carrier frequency is calculated using the symmetrical property of side-frequency components; the instantaneous frequency is computed to get the modulation frequency. The Cramer-Rao lower bound (CRLB) of parameter estimation of SFM is also been derived. Monte Carlo simulations show that the parameter estimation accuracy is acceptable when the SNR is above 6dB.

Keywords: Sinusoidal FM, Carson's Rule, Parameter estimation, Instantaneous frequency, CRLB

Issue 11, Volume 5, November 2009

Title of the Paper: A Novel Blind Digital Watermarking Technique for Stegano-Encrypting Information Using Nine-AC-Coefficient Prediction Algorithm with an Innovative Security Strategy


Authors: Chady El Moucary, Bachar El Hassan

Abstract: This paper presents a new methodology for data hiding using digital watermarking in the DCT Domain. The methodology relies on a new scheme for encrypting the data prior to the embedding stage. The key used for ciphering is almost of arbitrary length, type and format; this endows the watermark with a powerful, 3-level reinforced security structure. It is a blind-detector watermarking technique and the amount of the hidden data is increased by 60% compared with the traditional AC-Coefficients Prediction algorithm while sustaining a high level of transparency. Simulation results were carried out which demonstrated a promising PSNR, limited blocking artifacts, and a satisfactory level of the overall performance. The paper also presents an extensive survey of prominent digital-watermarking research outcomes in the WSEAS Transactions.

Keywords: Steganography, Encryption, Signal Scrambling, Increased Insertion Capacity, Digital Watermarking, Discrete Cosine Transform Domain, AC Coefficients Prediction

Title of the Paper: A Cumulant-Based Method for Gait Identification Using Accelerometer Data with Principal Component Analysis and Support Vector Machine


Authors: Sebastijan Sprager, Damjan Zazula

Abstract: In this paper a cumulant-based method for identification of gait using accelerometer data is presented. Acceleration data of three different walking speeds (slow, normal and fast) for each subject was acquired by the accelerometer embedded in cell phone which was attached to the person's hip. Data analysis was based on gait cycles that were detected first. Cumulants of order from 1 to 4 with different number of lags were calculated. Feature vectors for classification were built using dimension reduction on calculated cumulants by principal component analysis (PCA). The classification was accomplished by support vector machines (SVM) with radial basis kernel. According to portion of variance covered in the calculated principal components, different lengths of feature vectors were tested. Six healthy young subjects participated in the experiment. The average person recognition rate based on gait classification was 90.3±3.2%. A similarity measure for discerning different walking types of the same subject was also introduced using dimension reduction on accelerometer data by PCA.

Keywords: Gait Identification, Gait Recognition, Body Sensor, Accelerometer, Pattern Recognition, High-Order Statistics, Cumulants

Issue 12, Volume 5, December 2009

Title of the Paper: Multi-Class Support Vector Machine Classifier in EMG Diagnosis


Authors: Gurmanik Kaur, Ajat Shatru Arora, V. K. Jain

Abstract: The shapes of motor unit action potentials (MUAPs) in an electromyographic (EMG) signal provide an important source of information for the diagnosis of neuromuscular disorders. In order to extract this information from the EMG signals recorded at low to moderate force levels, it is required to: i) identify the MUAPs composed by the EMG signal, ii) cluster the MUAPs with similar shapes, iii) extract the features of the MUAP clusters and iv) classify the MUAPs according to pathology. In this work, three techniques for segmentation of EMG signal are presented: i) segmentation by identifying the peaks of the MUAPs, ii) by finding the beginning extraction point (BEP) and ending extraction point (EEP) of MUAPs and iii) by using discrete wavelet transform (DWT). For the clustering of MUAPs, statistical pattern recognition technique based on euclidian distance is used. The autoregressive (AR) features of the clusters are computed and are given to a multi-class support vector machine (SVM) classifier for their classification. A total of 12 EMG signals obtained from 3 normal (NOR), 5 myopathic (MYO) and 4 motor neuron diseased (MND) subjects were analyzed. The success rate for the segmentation technique used peaks to extract MUAPs was highest (95.90%) and for the statistical pattern recognition technique was 93.13%. The classification accuracy of multi-class SVM with AR features was 100%.

Keywords: Electromyography, motor unit action potentials, segmentation, pattern recognition, classification, multi-class support vector machine

Title of the Paper: Adaptive Thresholding of DFT Coefficients based on Probability Distribution of Additive Noise


Authors: Ondrej Raso, Miroslav Balik

Abstract: The proposed method of adaptive thresholding uses probability distribution of additive noise signal, by which the input signal is corrupted. The additive noise with non-uniformly distributed power spectral density can be reduced via normalization process. The method is focused on musical signal corrupted by the noise with relative high input signal-to-noise ratio ranging between 20 and 30 dB. The method uses the thresholding of coefficients of Discrete Fourier transform (DFT). Minimal signal distortion should be introduced by this method. In conclusion the method is tested for noise reduction efficiency and size of degradation of processed signal.

Keywords: Thresholding, Acoustic noise, Digital filters, Noise reduction, Discrete Fourier transform


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