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A Smart Mathematic Morphology Method for recognition and Understanding of Airfield

Wuhan University Journal of Natural Sciences 2005年第5期10卷 867-872页

作者： WANG Zhi-cheng TIAN Yan TIAN Jin-wen LIU Jian LIANG Chao-sheng TAO Wen-bin State Education Commission Key Laboratory for Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan430074 Hubei China Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Hubei China

A method used for recognition and understanding of airfield based on mathematical morphology is proposed in this paper. The new approach can he divided into three steps. First, to extract the typical geometric structure features of airfield, a segmentation method called recursive Otsu algorithm is employed on an airfield image. Second, thinning and shrinking algorithms are utilized to obtain the contour of airfield with single pixel and to remove diffused small particles. Finally, Radon transform is adopted to extract two typical and important components, primary and secondary runways of airfield exactly. At the same time, region growing algorithm is exploited to get the other components such as parking apron and garages. The experimental results demonstrate that the proposed method gives good performance.

关键词： mathematical morphology shrinking algorithm Radon transform Region growing

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Bidirectional Automated Branch and Bound Algorithm for Feature Selection

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Journal of Shanghai University(English Edition) 2005年第3期9卷 244-248页

作者：杨胜施鹏飞 Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 P. R. China

Feature selection is a process where a minimal feature subset is selected from an original feature set according to a certain measure. In this paper, feature relevancy is defined by an inconsistency rate. A bidirectional automated branch and bound algorithm is presented. It is a new complete search algorithm for feature selection, which performs feature deletion and feature addition in parallel. Its bound is determined by inconsistency rate of the original feature set, hence termed as ‘automated’. Experimental study shows that it is fit for feature selection.

关键词： feature selection pattern classification data mining machine learning.

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Investigation on traditional and modern ceramic documentation

Investigation on traditional and modern ceramic documentatio...

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IEEE International Conference on image processing

作者： M. Kampel H. Mara R. Sablatnig Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Vienna Austria

Archaeology is at a point where it can benefit greatly from the application of computer vision methods, and in turn provides a large number of new, challenging and interesting conceptual problems and data for computer science. This is true in particular in the study of ceramics - the most abundant and widespread of all archaeological finds. The traditional way of documenting archaeological sherds is to draw the profile line, which is the intersection of a sherd along the axis of symmetry. A profilograph is a mechanical device, which can directly acquire and transfer a profile line by pin-pointing the profile on a sherd to a computer. We developed a fully automated vision system, which is able to compute the profile line out of the acquired 3D model of the fragment. In this paper we want to give a thorough comparison between the traditional manual approach, the profilograph and our system and present an improvement of the robustness of our approach by finding circular rills on the fragments. Practical experiments have been undertaken at the excavation Tel Dor in Israel.

关键词： Ceramics Documentation Computer vision Pins pattern recognition image processing Automation Application software Computer science Machine vision

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A two-stage level set evolution scheme for man-made objects detection in aerial images

A two-stage level set evolution scheme for man-made objects ...

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Conference on Computer Vision and pattern recognition (CVPR)

作者： Guo Cao Xin Yang Zhihong Mao Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai P.R. China

ISBN: (纸本)0769523722

A novel two-stage level set evolution method for detecting man-made objects in aerial images is described. The method is based on a modified Mumford-Shah model and it uses a two-stage curve evolution strategy to get a preferable detection. It applies fractal error metric, developed by Cooper, et al. (1994) at the first curve evolution stage and adds additional constraint texture edge descriptor that is defined by using DCT (discrete cosine transform) coefficients on the image at the next stage. Man-made objects and natural areas are optimally differentiated by evolving the partial differential equation. The method artfully avoids selecting a threshold to separate the fractal error image, while an improper threshold often results in great segmentation errors. Experiments of the segmentation show that the proposed method is efficient.

关键词： Level set Object detection Hidden Markov models image segmentation Fractals Discrete cosine transforms pattern recognition Roads Layout Parameter estimation

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Efficient VLSI architecture for multi-dimensional discrete wavelet transform

Efficient VLSI architecture for multi-dimensional discrete w...

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MIPPR 2005: SAR and Multispectral image processing

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

Efficient VLSI architectures for multi-dimensional (m-D) discrete wavelet transform (DWT), e.g. m=2, 3, are presented, in which the lifting scheme of DWT is used to reduce efficiently hardware complexity. The parallelism of 2 m subbands transforms in lifting-based m-D DWT is explored, which increases efficiently the throughput rate of separable m-D DWT. The proposed architecture is composed of m2m-1 1-D DWT modules working in parallel and pipelined, which is designed to process 2m input samples per clock cycle, and generate 2m subbands coefficients synchronously. The total time of computing one level of decomposition for a 2-D image (3-D image sequence) of size N2 (MN2) is approximately N2/4 (MN2/8) intra- clock cycles (ccs). An efficient line-based architecture framework for both 2D+t and t+2D 3-D DWT is first proposed. Compared with the similar works reported in previous literature, the proposed architecture has good performance in terms of production of computation time and hardware cost. The proposed architecture is simple, regular, scalable and well suited for VLSI implementation.

关键词： VLSI circuits

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Error analysis and improvements of Spectral Angle Mapper (SAM) model

Error analysis and improvements of Spectral Angle Mapper (SA...

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MIPPR 2005: SAR and Multispectral image processing

作者： Du, Peijun Chen, Yunhao Fang, Tao Tang, Hong Department of RS and GISCi China University of Mining and Technology Xuzhou City Jiangsu Province 221008 China College of Resources Science Beijing Normal University Beijing 100875 Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China

Spectral Angle Mapper (SAM) model has got wide applications in hyperspectral Remote Sensing (RS) information processing. But Spectral Angle couldn't achieve satisfied performance in some cases because of its sensitivity to noises and uncertainty. Based on the analysis to traditional SAM algorithm, four types of errors and their impacts to spectral angle are investigated. In order to reduce the impacts of above errors, some improved algorithms are proposed and experimented. The first improved algorithm is grouping spectral angle algorithm. In this new algorithm all bands are divided into two sets by odd and even bands, that means two additional sub-vectors are created in addition to the original spectral vector. So three spectral angles will be computed and the minimum of three indexes is used as final index. The second improved algorithm is normalized spectral angle. In this way spectral angle is computed to the normalized vectors of two original vectors. Two approaches are used to normalize the spectral vector, and spectral angle is computed to the normalized vectors. This algorithm is able to decrease the impacts of random errors. The third algorithm is intersected spectral angle. Spectral angle is calculated by a spectral displacement strategy in this approach. That means a given displacement to change the corresponding bands of two spectral vectors is used and a spectral angle to the displaced vectors will be got. By this displacement strategy the impacts of band offset is reduced. Finally some experiments are used to test those improved algorithms. It proves that those new approaches can reduce and control the errors and improve the precision and reliability of similarity measure.

关键词： Remote sensing

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Two-band Infrared Data Fusion Method Based-on Fractal Dimension

Two-band Infrared Data Fusion Method Based-on Fractal Dimens...

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2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Yuqiu Sun Jinwen Tian Jian Liu Image Processing and Intelligence Control Key Laboratory of State Educational Ministry Institute of Pattern Recognition and Artificial IntelligenceHuazhong University of Science and Technology School of information and mathematics Yangtze University Dept.of Electronic Information and Enginery of Huazhong University of Science and Technology

ISBN: (纸本)0780394224

＜正＞Researches indicate that the gray-scale images mapped from most nature objects accord to the fractal Brown stochastic field which foundation is self-similarity,an image is self-similarity means the image is made up of copies of itself in a reduced *** fractal dimension can quantificational depict the fractal character and the property of an image. Therefore,a new method based-on fractal dimension to fuse mid-wave infrared images and long-wave infrared images is presented in the ***,images are decomposed into different scale using wavelet ***,the fractal dimensions of sub-images of original images are computed,and then take them as weight to fuse sub-images at the same level according to different ***,reconstruct the fused images by wavelet inverse *** experimental results imply that the method can effectively preserve the information of source images with a high contrast and may be very practical.

关键词： Fractals Infrared imaging Artificial intelligence Fuses Educational technology image reconstruction Layout Infrared detectors Intelligent control Process control

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A robust, real-time voice activity detection algorithm for embedded mobile devices

A robust, real-time voice activity detection algorithm for e...

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作者： Wu, Bian Ren, Xiaolin Liu, Chongqing Zhang, Yaxin Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China Motorola Labs. China Research Center 38F CITIC Sq. 1168 Nanjing Rd. W. Shanghai 200041 China

When an Automatic Speech recognition (ASR) system is applied in noisy environments, Voice Activity Detection (VAD) is crucial to the performance of the overall system. The employment of the VAD for ASR on embedded mobile systems will minimize physical distractions and make the system convenient to use. Conventional VAD algorithm is of high complexity, which makes it unsuitable for embedded mobile devices;or of low robustness, which holds back its application in mobile noisy environments. In this paper, we propose a robust VAD algorithm specifically designed for ASR on embedded mobile devices. The architecture of the proposed algorithm is based on a two-level decision making strategy, where there is an interaction between a lower features-based level and subsequent decision logic based on a finite-state machine. Many discriminating features are employed in the lower level to improve the robustness of the VAD. The two-level decision strategy allows different features to be used in different states and reduces the cost of the algorithm, which makes the proposed algorithm suitable for embedded mobile devices. The evaluation experiments show the proposed VAD algorithm is robust and contribute to the overall performance gain of the ASR system in various acoustic environments. © 2005 Springer Science+Business Media, Inc.

关键词： Speech recognition

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Fast and robust portrait segmentation using QEA and histogram peak distribution methods

Fast and robust portrait segmentation using QEA and histogra...

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International Conference on Intelligent Computing, ICIC 2005

作者： Liu, Heng Zhang, David Yan, Jingqi Li, Zushu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China Southwest University of Scientist and Technology Sichuan 621000 China Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong Institute of Intelligent Automation Chongqing University Chongqing 400044 China

image segmentation is kernel part of image analysis and processing. Fast and robust portrait segmentation and fusion is still a challenging problem by far. In this paper, we present two fast and robust methods to segment portrait in blue background. One method is threshold obtaining based on histogram peak distribution, the other is Quantum Evolution Algorithm (QEA) threshold searching based on group variance. Detailed experiments and comparison analyses are presented to demonstrate the performance of our methods. © Springer-Verlag Berlin Heidelberg 2005.

关键词： image segmentation

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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 2005

作者： Sun, Y.U.-Qiu Tian, Jin-Wen Liu, Jian School of Information and Mathematics Yangtze University Jingzhou 434023 China 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 430074 China State Education Commission Key Laboratory for Image Processing and Intelligent Control Dept. of Electronic Information and Enginery Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)078039092X

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 will 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. © 2005 IEEE.

关键词： pattern recognition

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