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Issue
1, Volume 5, January 2009
Title of the Paper:
Simple and Powerful Instrument Model for the Source Separation of Polyphonic
Music
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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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