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Feature Selection Based on Adaptive Fuzzy Membership Functions

自动化学报 2006年第4期32卷 496-503页

作者： XIE Yan-Tao SANG Nong ZHANG Tian-Xu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature selection algorithms with artificial neural networks(ANN)usually require normalization of input data,which will probably change some characteristics of original data that are important for *** overcome the problems mentioned above,this paper combines the fuzzification layer of the neuro-fuzzy system with the multi-layer perceptron(MLP)to form a new artificial neural ***,fuzzification strategy and feature measurement based on membership space are proposed for feature selection. Finally,experiments with both natural and artificial data are carried out to compare with other methods,and the results approve the validity of the algorithm.

关键词： Membership function feature selection architecture pruning artificial neural networks

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JOINT BLURRED image RESTORATION WITH PARTIALLY KNOWN INFORMATION

JOINT BLURRED IMAGE RESTORATION WITH PARTIALLY KNOWN INFORMA...

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： QING WU XING-CE WANG PING GUO Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

A new restoration method for joint blurred images with partially known information is proposed in this paper. The joint blur here is assumed to be motion blurs and defocus blur mixed together. Under the condition of two blur effects are supposed to be independent linear shift-invariant processes and motion blur parameter can be obtained with known information, a reduced update Kalman filter (RUKF) is used for degraded image restoration and the best defocus point spread function (PSF) parameter is determined based on the maximum entropy principle (MEP). Experimental results with real images show that the proposed approach works well.

关键词： PSF estimation Joint blurred image Reduced update Kalman filter Maximum entropy principle

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3D reconstruction of the coronary tree from two X-ray angiographic views

3D reconstruction of the coronary tree from two X-ray angiog...

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Medical Imaging 2006: image processing

作者： Sang, Nong Peng, Weixue Li, Heng Zhang, Zhen Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)0819464236

In this paper, we develop a method for the reconstruction of 3D coronary artery based on two perspective projections acquired on a standard single plane angiographic system in the same systole. Our reconstruction is based on the model of generalized cylinders, which are generated by sweeping a two-dimensional cross section along an axis in three-dimensional space. We restrict the cross section to be circular and always perpendicular to the tangent of the axis. Firstly, the vascular centerlines of the X-ray angiography images on both projections are semiautomatically extracted by multiscale vessel tracking using Gabor filters, and the radius of the coronary are also acquired simultaneously. Secondly, the relative geometry of the two projections is determined by the gantry information and 2D matching is realized through the epipolar geometry and the consistency of the vessels. Thirdly, we determine the three-dimensional (3D) coordinates of the identified object points from the image coordinates of the matched points and the calculated imaging system geometry. Finally, we link the consequent cross sections which are processed according to the radius and the direction information to obtain the 3D structure of the artery. The proposed 3D reconstruction method is validated on real data and is shown to perform robustly and accurately in the presence of noise.

关键词： image reconstruction

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An Efficient Face recognition System Using a New Optimized Localization Method

An Efficient Face Recognition System Using a New Optimized L...

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International Conference on pattern recognition

作者： H.R. Kanan K. Faez M. Ezoji Image Processing and Pattern Recognition Laboratory Electrical Engineering Department Amirkabir University of Technology슠 Tehran Iran

In this paper a system is developed for face recognition processes. Preprocessing and face localization is necessary to obtain a high classification rate in face recognition tasks. In this study after preprocessing of face images, for omitting the redundant information such as background and hair, the oval shape of face is approximated by an ellipse using shape information. Then the parameters (orientation and center coordinates) of this ellipse are optimized using genetic algorithm (GA). High order pseudo Zernike moment invariant (PZMI) which has useful properties is utilized to produce feature vectors. Also radial basis function neural network (RBFNN) with HLA learning rule has been used as a classifier. Simulation results on ORL database indicate that the error rate of proposed system which uses genetic algorithm for optimizing the face localization step is lower than an older system which described in (H. Haddadnia et al., 2003)

关键词： Face recognition Optimization methods Face detection Shape Genetic algorithms pattern recognition image processing Neural networks Feature extraction Hair

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Spam email filtering with bayesian belief network: using relevant words

Spam email filtering with bayesian belief network: using rel...

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IEEE International Conference on Granular Computing (GRC)

作者： Xin Jin Anbang Xu R. Bie Xian Shen Min Yin College of Information Science and Technology Beijing Normal University Beijing China Image Processing & Pattern Recognition Laboratory Beijing Normal University Beijing China

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Detection of small target in infrared image sequences using attention mechanism

Detection of small target in infrared image sequences using ...

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Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on

作者： Xun Yao Dehua Li Xianbin Sun Institute of pattern recognition and artificial intelligence Key Laboratory of Education Ministry for Image processing & Intelligence Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)0780393953

The requirement of algorithm for detecting small target in infrared image sequences is not only a high rate to identify the true target and a low false alarm rate, but also the computation efficiency. By employing the selective attention mechanism, biological visual system can interpret a complex incoming image in real time with limited hardware resources. Much evidence has suggested that the biological visual system processes information in a serial strategy which rapidly selects a small relevant region in scene for further complex and time consuming analysis. In this paper, a two component computation scheme is proposed to detect dim targets in infrared image sequences. In the first process stage, an efficient method is applied to extract the potential targets which are further identified in second phase, the true targets are detected, and the spurious objects are rejected. The attention-based approach reduces the computation complexity, while the other performance aspects are not traded off. Experimental results indicate that the proposed extraction and recognition modules exhibit excellent performance of detecting small target in infrared image sequences, especially in process speed aspect.

关键词： feature extraction image sequences infrared imaging biological visual system computation complexity computation efficiency false alarm rate feature extraction image recognition modules infrared image sequences selective attention mechanism small target d

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An Efficient Method for Face Localization and recognition in Color images

An Efficient Method for Face Localization and Recognition in...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Farshid Hajati Karim Faez Saeed Khoshfetrat Pakazad Pattern Recognition and Image Processing Laboratory EE Department Amirkabir University of Technology슠 Tehran Iran Electrical Engineering Department Amirkabir University of Technology슠 Tehran Iran

This paper introduces an efficient method for face localization and recognition in color images. The proposed method uses the location of eyes for computation and extraction of a face's bounding ellipse. In this way, parameters of a face's ellipse (center, orientation, major and minor axis), is computed by the location of eyes in a face image. In the next step, we apply Pseudo Zernike Moments (PZM), Zernike Moments (ZM) and Principal Component Analysis (PCA) for feature extraction. For classification of these feature vectors a new structure of RBF neural networks with a novel distance function is introduced and a new method for determination of RBF unit parameters is proposed. Finally, we compare the efficiency of the proposed system for three types of feature vectors (PZM, ZM and PCA). Results emphasize the high accuracy and efficiency of the PZM features proportion to other features (ZM and PCA) for use in the proposed recognition system.

关键词： Face recognition image recognition Color Face detection Skin Eyes Principal component analysis Humans Feature extraction Neural networks

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A DSP/FPGA - Based Parallel Architecture for Real-time image processing

A DSP/FPGA - Based Parallel Architecture for Real-time Image...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Luxin Yan Tianxu Zhang Sheng Zhong Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

A DSP/FPGA-based parallel architecture oriented to real-time image processing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnection network and the specific data communication protocol are implemented, which interconnect 3 DSPs (TMS320C6414) effectively. The measured performances in the prototype with the proposed parallel architecture, including inter-DSP data communication performance and system computing capacity, show high data transfer bandwidth (up to 400 Mbytes/s) with low latency as well as high image processing performance, which achieve a good balance for parallel image processing

关键词： Digital signal processing Field programmable gate arrays Parallel architectures image processing Data communication Computer architecture Multiprocessor interconnection networks Protocols Performance evaluation Prototypes

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Dualband Infrared images Target Detection Algorithm Based on Multiscale Morphology

Dualband Infrared Images Target Detection Algorithm Based on...

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2006 8th International Conference on Signal processing

作者： Yuqiu Sun Jinwen Tian Jian Liu School of Information and Mathematics Yangtze University State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial IntelligenceHuazhong University of Science and Technology

According to the features of mid-wave and long-wave infrared images,they are decomposed into morphology pyramid respectively based on the new multiscale mathematical morphology filters proposed in the *** features such as local maximum gray level and average gradient strength of every image are extracted at each level of morphology *** dualband infrared images based on fusion rule put forward in the paper,and then reconstruct original image and detect target using contrast threshold *** experiment results show that dualband infrared images target detection algorithm based on multiscale morphology algorithm is better than use mid-wave or long-wave infrared images detect targets alone.

关键词： image Dualband Infrared images Target Detection Algorithm Based on Multiscale Morphology Target

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RBF Network image Representation with Application to CT image Reconstruction

RBF Network image Representation with Application to CT Imag...

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International Conference on Computational Intelligence and Security

作者： Ping Guo Ming Hu Yunde Jia Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science Beijing Institute of Technology Beijing China Beijing Normal University Beijing Beijing CN China

ISBN: (纸本)1424406048

Radial basis function (RBF) neural network can be used as a universal approximator. In this paper, we propose a novel method to apply RBF net to reconstruct 2-dimensional computerized tomography (CT) images from a small amount of projection data. In the method, the cross-sectional image is represented by a RBF network, the unknown cross-sectional image vector is replaced by the function of the network's weight vector. As proved by us, the line integral of the weight matrix can be calculated providing the projections of the CT image are known. The ART method can be employed to obtain the final reconstructed CT image. Experiments show that the proposed method can obtain the better reconstructed image than the filtered back projection (FBP), and it is also more efficient than ART method alone

关键词： Radial basis function networks image representation Computed tomography image reconstruction Subspace constraints Matrix converters Equations Application software Laboratories Neural networks

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