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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Li, Shidong Ding, Mingyue Cai, Chao Institute for Pattern Recognition and Artificial Intelligence National Lab. for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China Hubei University for Nationalities Enshi Hubei 445000 China College of Life Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Traditional path planning methods are too slow to meet the real-time requirement in practical applications. In order to solve this problem, an idea of path net was proposed in this paper. The path planning procedure is divided into two steps: network segment planning and segment assembling. The first step was done with Fast Marching Method, including port selection of segment and network segment planning. Second step, the A* searching method was chosen to select segments for assembling. Experiments demonstrated that our method can obtain an optimal route in a few of seconds after the start and goal are given while several minutes are needed for traditional methods. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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Path planning using FMM with direction and curvature constrained

Path planning using FMM with direction and curvature constra...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and pattern recognition

ISBN: (纸本)9780819478092

It is difficult to meet both direction and curvature constraints for traditional Fast Marching (FM) method in path planning. Based on adjusting the cost function in Eiknoal equation-the control equation for FM, a new model for computing the integrated cost function was presented in this paper. A relationship formula about curvature radius was obtained and three kinds of adjusting strategies were given;two of them were used to modify the route to meet with the requires of turning constraint in this paper. Experiments showed that the improved model can be used to plan the path with FMM for agent such as unmanned aerial vehicle (UAV) or robot, which is limited to pass through the scene matching areas. And our preliminary experiments demonstrated that the strategies are feasible and efficient to obtain path with certain curvature radius. The model can also be used to represent the problem such as an aircraft flying in a flow field. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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A shadow detection method for remote sensing images using Affinity Propagation algorithm

A shadow detection method for remote sensing images using Af...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Huaiying Xia Xinyu Chen Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

Shadow detection in high spatial resolution remote sensing image is very critical for locating geographical targets. In this paper, we proposed a new shadow detection method using Affinity Propagation (AP) algorithm in the Hue-Saturation-Intensity (HSI) color space. Because the pixel matrix is a large-scale matrix, if we apply AP algorithm directly on the raw pixel space, it will be computation intensive to calculate the similarity matrix. To solve this problem, we propose to divide the matrix into several blocks and then applying AP to detect shadows in H, S and I components respectively. Then, three detected images are fused to obtain a final shadow detection result. Comparative experiments are performed for K-means and threshold segmentation methods. The experimental results show that higher detection accuracy of the proposed approach is obtained, and it can solve the problems of false dismissals of K-means and threshold segmentation method.

关键词： Remote sensing image segmentation Space technology Shape Color Layout Histograms image processing Spatial resolution Object detection

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Investigating visual feature extraction methods for image annotation

Investigating visual feature extraction methods for image an...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Rukun Hu Shuai Shao Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China The School of Computer Science and Technology Beijing Institute of Technology Beijing China

In order to investigate the performance of visual feature extraction method for automatic image annotation, three visual feature extraction methods, namely discrete cosine transform, Gabor transform and discrete wavelet transform, are studied in this paper. These three methods are used to extract low-level visual feature vectors from images in a given database separately, then these feature vectors are mapped to high-level semantic words to annotate images with labels in a given semantic label set. As it is more efficient to depict the visual features of an image by the feature distribution than to resort to image segmentation technology for semantic image blocks, this paper is going to find out which of the three feature extraction methods performs better in image annotation based on the distribution of feature vectors from the image. The performance of three different kinds of feature extraction method is fully analyzed, and it is found that discrete cosine transform method is more suitable for Gaussian mixture model in automatic image annotation.

关键词： Feature extraction Discrete wavelet transforms Discrete cosine transforms Shape image databases Spatial databases Visual databases image analysis Performance analysis Bayesian methods

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Feature Sharing Applied to Palmprint Identification

Feature Sharing Applied to Palmprint Identification

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International Conference on image and Graphics (ICIG)

作者： Ping Zheng Nong Sang State Key Laboratory of Multispectral Information Processing Technologies Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769552378;9780769538839

Palmprint identification is the means of recognizing an individual from the database using his or her palmprint features. This paper presents a palmprint recognition method by finding common features that can be shared across the classes (different persons), which is a welcome contrast to the existing approaches. At present almost all research is on low resolution images for civil and commercial applications, hence we trained classifiers working in similar feature spaces of the low dimensionality such as texture. In enrollment stage, we randomly select a certain number of samples each class as the training samples. After being preprocessed, the improved SIFT (Scale Invariant Feature Transformation) feature with SAX (Symbolic Aggregate approximation) representation is extracted from the image. The ECOC (Error Correct Output Code) matrix is obtained by layer joint boosting to select the best shared models and their shared features correspondingly. The sum of the weak classifiers which are constructed in each round of boosting turns into the strong classifier. In identification stage, query sample after being extracted features can be directly identified. The experimental results illustrate the effectiveness of the proposed approach.

关键词： Spatial databases Biometrics Boosting Fingerprint recognition Iris pattern recognition image recognition Feature extraction Graphics Laboratories

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Using Phase and Directional Line Features for Efficient Palmprint Authentication

Using Phase and Directional Line Features for Efficient Palm...

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Congress on image and Signal processing, CISP

In palmprint recognition, researchers can extract ridges, singular points and minutia points as features from high resolution images while in low resolution images they generally extract principal lines, wrinkles and texture. And now almost all research concentrates on low resolution images for civil and commercial applications. This is also the focus of this paper. In this paper, a new method based on 2D hybrid Log-Gabor filter, D-S evidence theory and ANOVA (Analysis Of Variance) method is proposed for feature extraction. In palmprint images, 2D hybrid Log-Gabor filter is constructed by a number of weighted 2D Log-Gabor filters with different orientations to extract texture mixed-phase feature. And the integration of ANOVA method and D-S evidence theory is then employed for detecting directional line feature by dealing with the uncertain weak edges and the difficulty in threshold selection from multi-images. Finally, a decision based on the measurement of a modified Hamming distance is obtained. Experiments on the Polyu-Online-Palmprint Database show competitive performance.

关键词： Authentication image resolution Filters Analysis of variance Feature extraction image edge detection image recognition Focusing Filtering theory Computer vision

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Classifier-Based Feature Fusion for Texture Discrimination

Classifier-Based Feature Fusion for Texture Discrimination

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International Conference on Information Engineering and Computer Science (ICIECS)

作者： Jianglin Ma Zhouwei Zhang Chengyi Wang Zhong Chen Remote Sensing Image Processing Laboratory Institute of Remote Sensing Applications Chinese Academy and Sciences Beijing China Institute for Pattern Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424449934

A classifier-based method to select and fuse grey level co-occurrence matrix (GLCM), Gaussian Markov random field (GMRF) and discrete wavelet transform (DWT) features to improve texture discrimination is presented. Feature selection via wrapper approaches is applied to find the optimal combination of texture features. The fused features have obtained higher discrimination accuracy compared with individual features. The curse of dimensionality is shown to affect discrimination accuracy, and feature selection and reduction helps obtain higher accuracy. Overall our proposed classifier-based method obtains the highest discrimination accuracy compared to other feature reduction methods such as principal component analysis (PCA) and linear discriminant analysis (LDA). Meanwhile GLCM features are found to produce higher discrimination accuracy than GMRF and DWT, and LDA is demonstrated to obtain higher discrimination accuracy than PCA.

关键词： Discrete wavelet transforms Linear discriminant analysis Signal processing algorithms Feature extraction Remote sensing Markov random fields Principal component analysis Classification algorithms Fuses Wavelet analysis

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A New Circle Targets Extraction Algorithm

A New Circle Targets Extraction Algorithm

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The First International Conference on Multimedia Information Networking and Security(第一届国际多媒体网络信息安全会议 MINES 2009)

作者： Chen Zhong Deng He Wang Guoyou Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Multi-Spectral Information Processing State Key Laboratory Wuhan P.R.China

According to the drawback of the traditional circle target extraction algorithm used by Hough Transform, such as computation complexity, low efficiency and etc, an new circle target extraction algorithm is proposed in this paper which can extract multiple circle targets with different radius at one time. First, the Average Absolute Difference is implemented to enhance the edge of the circle targets and suppress the noise of the background; Second, the locally self-adaptive segmentation algorithm is implemented to obtain the binary image. Thirdly, the thinning algorithm is implanted to obtain the single pixel edge of the circle targets and in order to reduce the computation times in the following process, a pruning algorithm is necessary; finally, a modified Hough transform algorithm is proposed to obtain the circle targets. The new circle targets have three advantages: low time consuming, high detection rate, robust to noise and fragmentary boundaries. The experimental results demonstrate that the new algorithm can extract the multiple circle targets quickly and accurately.

关键词： circle extraction hough transformation Average Absolute Difference thinning

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Modified majority voter for triple modular redundancy system

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Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology 2009年第SUPPL. 1期41卷 27-30页

作者： Zhang, Yi-Nan Guo, Ping Laboratory of Image Processing and Pattern Recognition Beijing Normal University Beijing 100875 China Laboratory of Computer Science Institute of Software The Chinese Academy of Sciences Beijing 100080 China

When applying formal majority voter in TMR (triple modular redundancy) fault tolerance system with two error injections, there is a problem that formal majority voter has a low rate of output. To solve this problem, we propose a modified majority voting model with special rules. In the situation of error injection, test result shows that compared with formal majority voter, modified majority voter has a higher rate of correct decision and a lower ratio of benign signals.

关键词： Fault tolerance

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Improving depth resolution of diffuse optical tomography with an exponential adjustment method based on maximum singular value of layered sensitivity

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Chinese Optics Letters 2008年第12期6卷 886-888页

作者：牛海晶郭平宋晓东蒋田仔 Image Processing and Pattern Recognition Laboratory Beijing Normal University School of Computer Science and Technology Beijing Institute of Technology School of Aerospace Science and Engineering Beijing Institute of Technology National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences

The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjustment method （EAM） based on maximum singular value of layered sensitivity is proposed. Optimal depth resolution can be achieved by compensating the reduced sensitivity in the deep medium. Simulations are performed using a semi-infinite model and the simulation results show that the EAM method can substantially improve the depth resolution of deeply embedded objects in the medium. Consequently, the image quality and the reconstruction accuracy for these objects have been largely improved.

关键词： Diagnostic radiography Electroabsorption modulators image quality Light absorption Medical imaging Optical tomography

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