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2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005

作者： Wang, Zhicheng Liu, Jian Tian, Jinwen Xie, Zeping State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong Univ. of Sci. and Tech. Wuhan 430074 China Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Tech. Wuhan 430074 China School of Life Sci. and Tech. Huazhong Univ. of Sci. and Tech. Wuhan 430074 China

ISBN: (纸本)0780387406

This paper introduces the new qualitative and quantitative methods, which can diagnose breast tumors. Qualitative methods include blood vessel display inside and outside of pathological changes part of breast, display of equivalent pixel curves at the part of pathological changes and display of breast tumor image edge. Accordingly, three feature extraction operators are proposed, i.e. the combination operators of anisotropic gradient and smoothing operator, an improved Sobel operator and an edge sharpening operator. Furthermore, quantitative diagnose approaches are discussed based on blood and oxygen contents according to abundant clinical data and pathological mechanism of breast tumors. The results of clinic show that the methods of combining qualitative and quantitative diagnose are effective for breast tumor images, especially for early and potential breast cancer. © 2005 IEEE.

关键词： Tumors

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An improved mapping method of buffer for line-based architecture of 2-D DWT

An improved mapping method of buffer for line-based architec...

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International Conference on Communications, Circuits and Systems (ICCCAS)

作者： Cheng-Yi Xiong Cheng-Jun Wang Jin-wen Tian Jian Liu Institute of Pattern Recognition & Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China College of Electronic Information Engineering South-Center University for Nationalities Wuhan China

ISBN: (纸本)0780390156

The number of arithmetic units used in the one-dimensional (1D) discrete wavelet transform (DWT) is the main consideration for reducing the area of VLSI implementation of 1D DWT, while the size of intermediate memory used for data buffering is another dominate factor of effecting hardware complexity of VLSI implementation for two-dimensional (2D) DWT. In this paper, we exploit the essential relationship between the size of temporal buffer (TB) required in the line-based architecture for 2D DWT (LBA2DDWT) and the number of registers used in the 1D DWT module, and present an improved method of mapping the registers used in the 1D DWT to the TB required in LBA2DDWT. Comparison results with the other design reported in previous literature demonstrate that, the proposed mapping method can reduce efficiently the size of memory required in LBA2DDWT.

关键词： Discrete wavelet transforms Registers Two dimensional displays Very large scale integration Hardware Convolution Pipeline processing Arithmetic Signal analysis Image processing

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Background suppression based-on wavelet transformation to detect infrared target

Background suppression based-on wavelet transformation to de...

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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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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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Blurred image recognition based on complex moment invariants

Blurred image recognition based on complex moment invariants

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IEEE International Conference on Image Processing

作者： Zhang Tianxu Liu Jin Institute for Pattern Recognition and Artificial Intelligence Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

ISBN: (纸本)0780385543

关键词： Image recognition Layout Convolution Radiometry Character recognition Target recognition Computer vision Biomedical imaging Degradation Cameras

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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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