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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yu-Qiu Sun Jin-Wen Tian Jian Liu State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China School of Information and Mathematics Yangtze University Jinzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China

Target detection and location in infrared clutter background is very important to infrared search and track system. Especially for small target detection in infrared image in background of sea and sky, there are no geometric and structure character to use. When targets such as ship and naval vessel sailing at long distance, they always appear around the sea-level line, and it is mixed with cloud and sea-wave clutter. It is difficult to segment and locate precisely. Background suppression based-on wavelet transformation is proposed in the paper. Wavelet decomposition makes it possible to analyze a signal both in time and frequency domains. In the paper infrared sea and key background images are processed. For their SNR is low and background is complex, using wavelet transformation decomposes an original image and extract approximate feature to reconstruct an image, which mainly includes background information. A new image would be obtained using background image subtracted from original image. There are mainly target and noise points left in the new image. By setting proper threshold, the target can be detected perfectly. At last, experiment results are given and show the method is practical.

关键词： Infrared detectors Object detection Infrared imaging Target tracking Marine vehicles Clouds Image segmentation Wavelet analysis Wavelet domain Signal analysis

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DSA image registration based on multiscale Gabor filters and mutual information

DSA image registration based on multiscale Gabor filters and...

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International Conference on Information and Automation (ICIA)

作者： Zhiguo Cao Xiaoxiao Liu Bo Peng Yiu-Sang Moon Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science and Engineering Chinese University of Hong Kong New Territories Hong Kong China

In clinical practice, digital subtraction angiography (DSA) is a powerful technique for the visualization of blood vessels in X-ray image sequences. Different with traditional DSA image registration processes, in our proposed image registration method, the control points are selected from the vessel centerlines using multiscale Gabor filters, and mutual information (MI) is then taken as the similarity criterion to find the correspondences. Experimental results demonstrate our algorithm efficiently yields satisfying registration result for DSA images.

关键词： Image registration Gabor filters Mutual information Biomedical imaging Angiography Visualization Displacement control Blood vessels Image sequences Pixel

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Blurred image recognition based on complex moment invariants

Blurred image recognition based on complex moment invariants

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2004 International Conference on Image processing, ICIP 2004

作者： Tianxu, Zhang Jin, Liu Institute for Pattern Recognition and Artifical Intelligence State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology China Institute for Pattern Recognition and Artifical Intelligence HuaZhong University of Science and Technology China

ISBN: (纸本)0780385543

An important class of radiometric degradations we are faced with often in practice is image blurring. Special attention is paid to the recognition of the blurred image by moment invariant approach. Some important rules of complex moments for the blurred image are presented. Based on these rules, a useful subset of moment invariants is introduced, that are not affected by the blur, rotation, scale, and translation of the images. The experiments have shown that these invariants can be successfully used in recognition of the blurred image. ©2004 IEEE.

关键词： pattern recognition

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Robust Watermarking Scheme with Side Information and Template Matching Mechanism

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High Technology Letters 2004年第2期10卷 30-33页

作者：郭捷 Fang Tao Shi Pengfei Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai 200030 P.R.China The State Key Laboratory of Information Security Chinese Academy of Sciences Beijing 100039 P.R.China

Digital watermarking has been proposed for the copyright protections of multimedia products. In this paper, a robust and blind watermarking scheme is presented. The concept of communication with side information is applied at the encoder to improve the probability of detection within acceptable fidelity, while the template matching technique is employed to estimate the undergone attacks in attacking channel. This scheme is optimized by the optimal design of the encoder to match with the media content and the decoder to adapt to the attack channel state. Experiments show that our method is robust against some common attacks such as filtering, compression, rotation, scaling, cropping and translation. It can be applied to both color and gray images.

关键词：数字水印边缘信息模板匹配多媒体水印嵌入

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A fast VLSI architecture for two-dimensional discrete wavelet transform based on lifting scheme

A fast VLSI architecture for two-dimensional discrete wavele...

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2004 7th International Conference on Solid-State and Integrated Circuits Technology Proceedings, ICSICT 2004

作者： Xiong, Chengyi Tian, Jinwen Liu, Jian Institute of Pattern Recognition and Artificial Intelligence Key Laboratory of Eduaction Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China College of Electronic Information Engineering South-Center University for Nationalities Wuhan 430074 China

This paper proposes a novel fast architecture for two-dimensional discrete wavelet transform by using lifting scheme. The parallel and embedded decimation techniques are employed to optimize the architecture, which is mainly composed of two horizontal filter modules and one vertical filter module, working in parallel and pipeline fashion with 100% hardware utilization. The architecture is designed to generate two outputs at one working clock cycle, with every two subbands coefficients alternately. The total time of computing J levels of decomposition for N×N image is approximately 2N2(I-4 J)/3 clock cycles. In comparison with the other devices reported in previous literature, the design has many advantages including lower hardware complexity and area and power efficient. The design is also fast, regular and simple, as well as well suited for VLSI implementation. © 2004 IEEE.

关键词： VLSI circuits

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Image denoising using wavelet and support vector regression

Image denoising using wavelet and support vector regression

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International Conference on Image and Graphics (ICIG)

作者： Hui Cheng Qiuze Yu Jinwen Tian Jian Liu Institute for Pattern Recognition and Aritificial Intelligence Key Laboratory of Education Ministry for Image Processing & Intelligence Control Huazhong University of Science and Technology Wuhan China

Wavelet image denoising has been well acknowledged as an important method of denoising in image processing. This paper describers a new method for the suppression of noise in image by fusing the wavelet denoising technique with support vector regression (SVR). Based on the least squares support vector machine (LS-SVM), a new denoising operators used in the wavelet domain are obtained. Simulated noise images are used to evaluate the denoising performance of the proposed algorithm along with the other wavelet-based denoising algorithm. Experimental results show that the proposed denoising method outperforms standard wavelet denoising techniques in terms of the signal-to-noise ratio and the prevented edge information in most cases. It also achieves better performance than the median filter.

关键词： Image denoising Noise reduction Support vector machines Wavelet domain Wavelet transforms Wavelet analysis Support vector machine classification Wavelet coefficients Artificial intelligence Image processing

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Greeting from the Conference Chairman

Greeting from the Conference Chairman

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International Conference on Signal processing Proceedings (ICSP)

作者： Baozong Yuan National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

Presents the welcome message from the conference proceedings.

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An SVM-based small target segmentation and clustering approach

An SVM-based small target segmentation and clustering approa...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Sheng Zheng Jian Liu Jin-Wen Tian State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)0780384032

Segmentation and clustering of infrared small target images in a sky or sea-sky background is considered in this paper, which is the preprocessing part of the detection and recognition of the moving small targets in an infrared image sequence. The infrared image intensity surface is well fitted by the least squares support vector machines (LS-SVM), and then the maximum extremum points are detected on the well fitted intensity surface by convolving the image with the second order directional derivative operators deduced from the mapped LS-SVM with mixtures of kernels. With the coarse locations, the possible targets are extracted by the clustering analysis. The computer experiments are carried out for the real and simulated sky and sea-sky infrared images. The experimental results demonstrate the proposed approach is effective.

关键词： Infrared detectors Infrared imaging Image segmentation Sea surface Image recognition Target recognition Image sequences Least squares methods Support vector machines Kernel

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One efficient facet-based small target detection technique

One efficient facet-based small target detection technique

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International Conference on Signal processing Proceedings (ICSP)

作者： Sheng Zheng ChengYi Xiong JinWen Tian Jian Liu State Education Commission Key Laboratory of Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

This paper presents a method for the detection of small objects from the infrared images. The detection is performed on the intensity surface well fitted by the cubic facet model. The small target energy distribution presents as a convex surface on the image intensity surface and the target center is the maximal extremum points of the convex surface. According to the extremum theory, the possible small target position is analytically determined by directly convolving the original image with the derivative operators deduced from the bivariate cubic function. With the available coarse target locations, the potential target is separated from the background by examining the intensity features of the target cluster. Experimental results on the sample infrared images demonstrate the proposed algorithm provides a robust and efficient performance.

关键词： Face detection Object detection Target tracking Infrared detectors Surface topography Infrared imaging Maintenance Intelligent control pattern recognition Artificial intelligence

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Multiscale centerline extraction of angiogram vessels using gabor filters

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3314卷 570-575页

作者： Sang, Nong Tang, Qiling Liu, Xiaoxiao Weng, Wenjie Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

In this paper, we propose a new automated approach to extract the centerlines from 2-D angiography. The centerline extraction is the basis of 3-D reconstruction of the blood vessels, so the accurate localization of centerlines counts for much. The characteristics of multiscale Gabor even filter, flexible frequency bands and enhancement effects, are fully utilized to detect centerlines of the blood vessels in various size. © Springer-Verlag 2004.

关键词： Blood vessels

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