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7th International symposium on signal processing and Its Applications

作者： Sun, H Maitre, H Guan, B Wuhan Univ Sch Elect Informat LIESMARS Wuhan 430072 Peoples R China

ISBN: (纸本)0780379462

A new iterative processing for image restoration is proposed based on the turbo iterative principle. For this purpose, two uncorrelated component images issued from an original image are differently filtered and the pieces of information extracted from both filters are mutually exchanged in the iterative process. This scheme has achieved much better performances and reduced computational cost in restoring images with both additive and multiplicative (such as in SAR radar images) noise model.

关键词： image reconstruction

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AdaBoost in basketball player identification

AdaBoost in basketball player identification

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13th ieee International symposium on computational intelligence and Informatics (CINTI)

作者： Ivankovic, Z. Markoski, B. Ivkovic, M. Radosav, D. Pecev, P. Univ Novi Sad Tech Fac Mihajlo Pupin Zrenjanin Serbia Univ Novi Sad Fac Sci Novi Sad Serbia

ISBN: (纸本)9781467352062;9781467352055

Video materials contain huge amount of information. Their storage in databases and analysis by various algorithms represents an area that constantly develops. This paper presents the process of analysis of basketball games by AdaBoost algorithm. This algorithm is mainly used for face recognition and body parts recognition. It consists of a linear combination of weak classifiers. In this paper, stumps were used as weak classifiers. The aim of this research is to assess the accuracy of this algorithm when applied in players' identification at basketball games. Capabilities of AdaBoost were examined when applied to video footage from single moving camera, and when these footages were not previously treated by any other algorithm. The first training was performed by entire images of basketball players, whereas the second training was performed by using the images of the head and torso. By applying the algorithm to the given set of images that include head and torso, the algorithm obtained an accuracy of 70.5%. Experimental results have shown that training on the set of entire body images was not possible due to large amount of background that goes into the training, and which represents noise in training process. This accuracy could be increased by applying filters that would remove background from images and leave just basketball players. By applying those filters, the amount of noise in the training data would be significantly reduced.

关键词： cameras face recognition image classification learning (artificial intelligence) sport video signal processing

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CO-OCCURRENCE ANALYSIS OF SPEECH WAVEFORMS

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ieee TRANSACTIONS ON ACOUSTICS SPEECH AND signal processing 1985年第1期33卷 5-30页

作者： TERZOPOULOS, D Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA

The co-occurrence matrix, a two-dimensional histogram of pairs of sample amplitudes, is explored as a representation of the digital speech waveform. Co-occurrence matrix representations support a hypothesis-testing approach to digital speech analysis. This approach is pursued in the formulation of a quantitative (chi-square) measure of sample amplitude dependence, based on co-occurrence matrices. This measure, which is higly sensitive to quasi-periodicity, is shown to lead to a good estimator of the pitch period of voiced speech. Co-occurrence matrix representations are employed in conjunction with pattern classification methods in experiments involving the voiced-unvoiced-silence analysis of speech, and in an experimental pitch extraction algorithm which is tested on continuous speech.

关键词： Speech analysis Histograms Testing Pattern analysis Algorithm design and analysis Speech recognition computational efficiency Digital images image analysis image texture analysis

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A new approach to improving fractal image compression times

A new approach to improving fractal image compression times

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4th International symposium on image and signal processing and Analysis

作者： Zumbakis, T Valantinas, J Kaunas Univ Technol Kaunas Lithuania

ISBN: (纸本)953184089X

The paper presents a new approach to improving fractal image compression times. The range blocks and corresponding domain blocks are categorized in accordance with their smoothness level. The searching is carried out between the same (or, neighbouring) smoothness classes for range-domain comparisons which significantly reduces the computational complexity. Theoretical and experimental results show that extremely high compression time savings are achieved for images of size 512x512.

关键词： image compression

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X Ray image Enhancement Technology for Steel Pipe Welding Based on Hopfield Neural Network

X Ray Image Enhancement Technology for Steel Pipe Welding Ba...

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2nd International symposium on computational intelligence and Design

作者： Gao Weixin Sun Lianmin Mu Xiangyang Tang Nan Wu Xiaomeng Xian Shiyou Univ Sch Elect Engn Xian Peoples R China Univ Kitakyushu Dept Informat & Media Engn Kitakyushu Fukuoka Japan

ISBN: (纸本)9780769538655

Hopfield neural network is utilized to enhance x-ray image of thick steel pipe welding, and a gray mapping matrix is constructed to replace traditional gray transformation curves and functions in this paper. The maximum dimension of the gray mapping matrix is 256(X)256, so the calculation time has little relation with the size of the image. The criterion function of image quality is used to evaluate the quality of the transformed image. In proposed approach, the problem of image enhancement is transformed to an optimization problem, so the normalization of gray values for each pixel is not necessary. The energy function that improves the performance of image enhancement is also given for Hopfield neural network.

关键词： Hopfield Neural Network image processing image Hencing

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A multi-layer neural network and an adaptive linear combiner for on-line harmonic tracking

A multi-layer neural network and an adaptive linear combiner...

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ieee International symposium on Intelligent signal processing

作者： Zouidi, Abdelaziz Fnaiech, Farhat AL-Haddad, Kamal Univ Tunis Ecole Super Sci & Tech Tunis Equipe Rech Signal Image & Commande Intelligent S 5 Av Taha Hussein Tunis 1008 Tunisia CRC ECPE Ecole Technol Super Quebec City PQ H3C 1K3 Canada

ISBN: (纸本)9781424408290

Intelligent techniques of harmonic detection or estimation are nowadays of a great interest in power system applications, their ability to deal with high non-linearities attract researchers to investigate the performance of these methods mainly based on artificial intelligence namely using artificial neural networks. In the literature many harmonic detection or estimation methods were presented, in this paper we focus on a new idea to apply an adaptive linear neuron (ADALINE) and a multi-layer artificial neural net work (M-LANN) [5] to estimate the fundamental component and the total harmonic content of a distorted signal.

关键词： harmonic detection artificial intelligence artificial neural networks

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image fusion method based on improved NSCT transform and PCNN model 9

Image fusion method based on improved NSCT transform and PCN...

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9th International symposium on computational intelligence and Design (ISCID)

作者： Gong, Jiamin Wang, Beibei Qiao, Lin Xu, Jiachi Zhang, Zhengjun Xian Univ Posts & Telecommun Sch Elect Engn Xian 710121 Peoples R China Xian Univ Posts & Telecommun Sch Commun & Informat Engn Xian 710121 Peoples R China

ISBN: (纸本)9781509035588

Multi-source image fusion has been the hotspot of research in recent years, in order to make the fusion results more consistent with human vision and computer processing, many classical algorithms have been proposed, such as contourlet transform, non-subsampled contourlet transform (NSCT) and so on. On this basis, this paper proposes an improved fusion method of infrared and visible images based on NSCT transform and pulse coupled neural network (PCNN). The basic idea is that the source images are decomposed by NSCT to obtain low frequency and high frequency bands, low frequency components use the regional variance saliency fusion method of adaptive threshold weighted, high frequency components use the PCNN method, and high frequency subband coefficients are directly used as external inputs of PCNN neurons. Experimental results show that the fused image has higher clarity and richer useful information. Both subjective and objective performance indicators are better than the traditional algorithm.

关键词： image fusion Infrared image Visible image NSCT transform PCNN model

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Performance of Overloaded MIMO-OFDM System with Repetition Code

Performance of Overloaded MIMO-OFDM System with Repetition C...

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International symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Matsuoka, Hikari Doi, Yoshihito Yabe, Tatsuro Sanada, Yukitoshi Keio Univ Dept Elect & Elect Engn Yokohama Kanagawa Japan

ISBN: (纸本)9781479961207

This paper investigates the performance of an overloaded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with a repetition code. It has been demonstrated that diversity with block coding prevents the performance degradation induced by signal multiplexing. However, the computational complexity of a joint decoding scheme increases exponentially with the number of multiplexed signal streams. Thus, this paper proposes the use of a repetition code in the overloaded MIMO-OFDM system. In addition, QR decomposition with M-algorithm (QRM) maximum likelihood decoding (MLD) is applied to the decoding of the repetition code. QRM-MLD significantly reduces the amount of joint decoding complexity. In addition, virtual antennas are employed in order to increase the throughput that is reduced by the repetition code. It is shown that the proposed scheme reduces the complexity by about 1/48 for 6 signal streams with QPSK modulation while the BER degradation is less than 0.1dB at the BER of 10(-3).

关键词： MIMO communication OFDM modulation error statistics maximum likelihood decoding BER degradation QR decomposition with M-algorithm QRM maximum likelihood decoding block coding computational complexity joint decoding scheme multiple-input multiple-output multiplexed signal streams orthogonal frequency division multiplexing overloaded MIMO-OFDM system repetition code signal multiplexing virtual antennas computational modeling Decoding Encoding Joints Multiplexing Throughput Transmitting antennas repetition coding Orthogonal frequency division multiplexing Block codes multiple input multiple output systems maximum likelihood decoding MULTIPLEXOR DECODING transmitting antennas MIMO communication Throughput decoding scheme computational modeling Joints Joints complexity classes

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The Performance Research of Vice Peak Restrained Acquisition Algorithm for MBOC signal 7

The Performance Research of Vice Peak Restrained Acquisition...

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7th International symposium on computational intelligence and Design (ISCID)

作者： Liu, Fang Huang, Zhen Feng, Yongxin Zhang, Na Shenyang Ligong Univ Sch Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9781479970056

With the development of the spread spectrum communication technology a new MBOC modulation technology has come into being. Its main autocorrelation peak is sharper than that of BOC signal, so it helps to improve the signal acquisition and tracking accuracy. But the multipeaks characteristics of its autocorrelation function, especially the vice peak characteristic, cause the ambiguous problems of acquisition processing. Thus, the acquisition technology research is carried out on this ambiguous problem from the perspective of vice peck inhibition. And give the best acquisition parameters analyzed for more effective of vice peak of autocorrelation function elimination method and BPSK - like algorithm. And then compare the performance among the vice peak of autocorrelation function elimination method, the whole band acquisition algorithm and BPSK - like algorithm from the perspective of vice peak restrain, main autocorrelation peak and acquisition time, thus, the effective and reasonable acquisition advices are given.

关键词： MBOC Main peak Ambiguous Vice peak restrain Acquisition

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Illumination field estimation through background detection in optical microscopy

Illumination field estimation through background detection i...

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ieee symposium on computational intelligence in Bioinformatics and computational Biology

作者： Gherardi, Alessandro Bevilacqua, Alessandro Piccinini, Filippo University of Bologna Italy University of Bologna Italy

ISBN: (纸本)9781424498970

Automated microscopic image analysis techniques are increasingly gaining attention in the field of biological imaging. The success of these applications mostly depends on the earlier image processing steps applied to the acquired images, aiming at enhancing image content while performing noise and artifacts removal. One such artifact is the vignetting effect that in general occurs in most imaging sensors due to an uneven illumination of the scene being imaged. As a consequence, images are usually lighter near the optical center and darker at image borders. This effect is particularly evident when stitching images into a mosaic in order to increase the field of view of the microscope. The existing approaches deal with either the parametric model of the known light distribution or the estimation of the illumination field based on just one image or a sequence of empty-field images. These approaches are only feasible when the acquisition apparatus is at one's disposal. We propose a non parametric and general purpose approach, without using prior information about the light distribution, where the illumination field is estimated from the background, that is built automatically stemming from a sequence of images containing even the objects of interest. © 2011 ieee.

关键词： image enhancement

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