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Fast and precise method of eyes location

Guangdianzi Jiguang/Journal of Optoelectronics Laser 2005年第4期16卷 479-483页

作者： Yu, Wei-Wei Teng, Xiao-Long Liu, Chong-Qing Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China

Fast radial symmetry transform can fast detect points of interest and is the improvement of generalized symmetry transform. Firstly, the location of eyebrows is estimated. According to the location of eyebrows, in certain range that possibly includes eyes, fast radial symmetry transform is used to detect black points of interest. After rectifying a deviation and according to the geometrical features, the eyes candidates are selected and the precise location can be decided by pupil model. The experiments in ORL and SJTU-IPPR fact database show the algorithm is effective and can be used in real-time system.

关键词： Face recognition

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Real-time signal processing system for target tracking based on ADSP21060 and FPGA

Real-time signal processing system for target tracking based...

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International Conference on Communications, Circuits and Systems (ICCCAS)

作者： Guangzhou Zhao Tianxu Zhang State Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)0780390156

This paper presents a novel real-time signal processing system using for target tracking, it uses both ADSP21060 and FPGA to attain high performance and high-speed image processing. It analyses the flexible hardware architecture based on the idea of reconfigurability and modularization, and discusses three main modules and extensibility of the hardware system. Then the implementation of the image pre-processing and target intelligent tracking algorithm is discussed in detail. The experimental result shows that the system processing rate reaches 30 frames per second. The system can automatically detect targets and output the tracking information in real-time.

关键词： Real time systems Signal processing Target tracking Field programmable gate arrays Digital signal processing Hardware Logic arrays Signal processing algorithms image processing image analysis

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Outlier detection by weighted mercer-kernel based fuzzy clustering algorithm

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Iranian Journal of Electrical and Computer Engineering 2005年第2期4卷 129-136页

作者： Shen, Hongbin Yang, Jie Dong, Yifei Wang, Shitong College of Computer and Information Engineering Hohai University Changzhou Jiangsu China Department of Image Processing and Pattern Recognition Jiaotong University Shanghai China School of Computer Science and Engineering University of New South Wales Australia School of Information Southern Yantze University Wuxi Jiangsu China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China IEEE Institute of National Automation Department of Information Southern Yangtse University Polytechnic University of Hongkong Advanced Computing Research Center Bristol University United Kingdom

Outliers are data values that lie away from the general cluster of other data values. Detecting the outliers of a dataset is an important research topic for data cleaning and finding new useful knowledge in many research areas, i.e. data mining, pattern recognition, etc. In the past decades, many useful algorithms were proposed in the literature. In this paper, a new fuzzy kernel-clustering algorithm with outliers (FKCO) is presented to locate critical areas that are often represented by only a few outliers. Theoretic analysis also shows that FKCO can converge to a local minimum of the objective function. Finally, based on the information theory, a new criterion for finding outliers is also proposed. Simulations of different types of datasets demonstrate the feasibility of this new method. © 2005 JD.

关键词： Fuzzy control

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Support value based fusing images with different focuses

Support value based fusing images with different focuses

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International Conference on Machine Learning and Cybernetics (ICMLC)

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

Many vision-related processing tasks, including edge detection and image segmentation, can be performed more easily when all objects in the scene are in good focus. However, in practice, this may not be always feasible as optical lenses, especially those with long focal lengths, only have a limited depth of field. One classical approach to recover an everywhere-in-focus image is to use Laplacian pyramid image fusion. First, several source images with different focuses of the same scene are taken and decomposed into the low/high-frequency components image sequences. Within these decompositions, the high-frequency components image sequences with the largest magnitude are selected at each pixel location. Finally, the fused image can be recovered from the decomposed components image sequences. In the support vector machine (SVM), the pixels with larger support values have a physical meaning in the sense that they reveal relative more importance of the data points for contributing to the SVM model. In this paper, we use Laplacian pyramid for the multi resolution decomposition, and then replace the traditional salient features by support values of the mapped least squares (LS)-SVM for fusing image. Experimental results illustrate that the proposed method outperforms the traditional approach.

关键词： Focusing image sequences Support vector machines Layout Laplace equations image edge detection image segmentation Optical sensors Lenses image fusion

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Three-dimensional motion analysis of mitral valve leaflet in children with congenital heart disease and its clinical significance: a pilot study

Three-dimensional motion analysis of mitral valve leaflet in...

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Computers in Cardiology (CinC)

作者： K. Sun X. Yan L.P. Yao Q. Guo L.P. Wu Y.F. Shang Shanghai Children's Medical Center XinHua Hospital Affiliated to Medical School of Shanghai Jiao Tong University Shanghai China Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

This study is to quantitatively evaluate abnormal movement of mitral apparatus (MA) in patient with congenital mitral valve regurgitation using self-designed three dimensional motion analyses software and enable doctors to intuitionistic and "en-face" visualize the mitral valve's movement by using pseudocolor coding of the moving velocity of mitral valve leaflet. Initial evaluation of the software was conducted in 20 children with congenital mitral valve regurgitation (MR) including 10 children with mild MR and 10 children with moderate to severe MR. Results showed that, the moving velocity of the rough zone of mitral valve during systolic phase in children with moderate to severe MR is much high than that in control group. It's indicated that three dimensional motion analysis of mitral valve could emerge to be a new potential useful parameter for evaluation the truly mechanism of MR

关键词： Motion analysis Heart valves Cardiac disease Pediatrics Velocity control Echocardiography Biomedical imaging image coding Hospitals image processing

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Using string kernel to predict signal peptide cleavage site based on subsite coupling model (vol 28, pg 395, 2005)

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AMINO ACIDS 2005年第3期29卷 301-301页

作者： Wang, M Yang, J Chou, KC Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Microsoft Research Asia Beijing China Institute of Bioinformatics and Drug Discovery Tianjin China Gordon Life Science Institute San Diego U.S.A.

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Optimal sub-shape models by minimum description length

Optimal sub-shape models by minimum description length

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Conference on Computer Vision and pattern recognition (CVPR)

作者： G. Langs P. Peloschek H. Bischof Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Department of Clinical Radiology Vienna Medical University Vienna Austria

Active shape models are powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowledge in an efficient and gainful way. However, due to the linearity of PCA, non-linearities like rotations or independently moving sub-parts in the data can deteriorate the resulting model considerably. Although non-linear extensions of active shape models have been proposed and application specific solutions have been used, they still need a certain amount of user interaction during model building. In this paper the task of building/choosing optimal models is tackled in a more generic information theoretic fashion. In particular, we propose an algorithm based on the minimum description length principle to find an optimal subdivision of the data into sub-parts, each adequate for linear modeling. This results in an overall more compact model configuration. Which in turn leads to a better model in terms of modes of variations. The proposed method is evaluated on synthetic data, medical images and hand contours.

关键词： Active shape model Biomedical imaging Principal component analysis Computer vision Linearity Polynomials pattern recognition Computer graphics Radiology image processing

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A combining method for tumors detection from near-infrared breast imaging

A combining method for tumors detection from near-infrared b...

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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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A New Approach of Color image Quantization

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通讯和计算机（中英文版） 2005年第3期2卷 72-76页

作者： HU Xinrong WANG Tianzhen LI Dehua Institute for Pattern Recognition and Artificial Intelligence State Education Commission Laboratory for Image Processing and Intelligence Control HuaZhong Univ. of Science＆Technology WuHan 430074 China Dept. of Computer Science ＆Technology Wuhan Institute of Science＆Technology WuHan 430074 China Institute of linage Processing WuHan Univ. of Technology Wuhan 430070China

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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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