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International Conference on pattern recognition

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

ISBN: (纸本)0769525210

In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are related to active appearance models, but instead of modelling the entire texture of an object they represent image texture by means of local descriptors. The approach has advantages with complex image data like anatomical structures that exhibit high texture variation with limited relevance for the recognition of the object location. Experimental results and the comparison to AAMs on different data sets indicate that active feature models can improve search speed and result accuracy, considerably

关键词： Shape Active appearance model Biomedical imaging image texture image edge detection image texture analysis computer graphics pattern recognition image processing Radiology

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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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Feature points matching algorithm in DSA image registration

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Journal of Computational Information Systems 2013年第1期9卷 113-120页

作者： Zhang, Fan Hou, Yabin Cui, Yanbin Zhang, Xinhong Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China Equipment Management Department Henan University Kaifeng 475001 China College of Computer and Information Engineering Henan University Kaifeng 475001 China

Motion artifacts of digital subtraction angiography (DSA) are usually corrected by image registration. image registration is the process of transforming different sets of feature points into one coordinate system. Mismatches between the two sets of feature points will directly affect the image registration, and thus cause a lot of artifacts in the subtraction images. In this paper, a feature points matching algorithm is proposed. The similarity measure of feature point neighborhood is used to find the corresponding feature points, and delete a large number of non-existent corresponding feature points. It will improve image registration of DSA effectively. © 2013 Binary Information Press.

关键词： image registration

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Kalman filtering based watermarking algorithm

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Journal of Information and Computational science 2009年第6期6卷 2193-2198页

作者： Zhang, Fan Ding, Aiping Shang, Dongfang Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China College of Computer and Information Engineering Henan University Kaifeng 475001 China Department of Information Engineering Yellow River Conservancy Technical Institute Kaifeng 475001 China

A digital watermark algorithm based on Kalman filter and image fusion is proposed. Digital watermarking is considered as a process of image fusion. Watermark image and original image are unified in a new state equation, and then the corresponding measurement equation is built. Digital watermark is embedded into original image according to the optimal estimation in the case of minimum estimation error variance. Experimental results show that the proposed algorithm has a good robustness and invisibility. © 2009 Binary Information Press.

关键词： Kalman filters

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An evolutionary lion optimization algorithm-based image compression technique for biomedical applications

An evolutionary lion optimization algorithm-based image comp...

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作者： Geetha, Karuppaiah Anitha, Veerasamy Elhoseny, Mohamed Kathiresan, Shankar Shamsolmoali, Pourya Selim, Mahmoud M. Department of Computer Science & Engineering MIET Engineering College Tamilnadu India Department of Computer Science and Engineering Imayam College of Engineering Anna University ChennaiTamilnadu India Faculty of Computers and Information Mansoura University Mansoura Egypt Scientific Group for Research and Technology Cairo Egypt Department of Computer Applications Alagappa University Karaikudi India Huawei Technologies Corporate Shanghai China. & Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Department of Mathematics Al-Aflaj College of Science and Human Studies Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia

Recently, medical image compression becomes essential to effectively handle large amounts of medical data for storage and communication purposes. Vector quantization (VQ) is a popular image compression technique, and the commonly used VQ model is Linde–Buzo–Gray (LBG) that constructs a local optimal codebook to compress images. The codebook construction was considered as an optimization problem, and a bioinspired algorithm was employed to solve it. This article proposed a VQ codebook construction approach called the L2-LBG method utilizing the Lion optimization algorithm (LOA) and Lempel Ziv Markov chain Algorithm (LZMA). Once LOA constructed the codebook, LZMA was applied to compress the index table and further increase the compression performance of the LOA. A set of experimentation has been carried out using the benchmark medical images, and a comparative analysis was conducted with Cuckoo Search-based LBG (CS-LBG), Firefly-based LBG (FF-LBG) and JPEG2000. The compression efficiency of the presented model was validated in terms of compression ratio (CR), compression factor (CF), bit rate, and peak signal to noise ratio (PSNR). The proposed L2-LBG method obtained a higher CR of 0.3425375 and PSNR value of 52.62459 compared to CS-LBG, FA-LBG, and JPEG2000 methods. The experimental values revealed that the L2-LBG process yielded effective compression performance with a better-quality reconstructed image. © 2020 John Wiley & Sons Australia, Ltd

关键词： Vector quantization

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Motion constraint patterns

Motion constraint patterns

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IEEE Workshop on Qualitative Vision

作者： C. Fermuller Department for Pattern Recognition and Image Processing Institute for Automation Technical University of of Vienna Vienna Austria Computer Vision Laboratory Center for Automation Research University of Maryland College Park MD USA

The problem of egomotion recovery has been treated by using as input local image motion, with the published algorithms utilizing the geometric constraint relating 2-D local image motion (optical flow, correspondence, derivatives of the image flow) to 3-D motion and structure. Since it has proved very difficult to achieve accurate input (local image motion), a lot of effort has been devoted to the development of robust techniques. A new approach to the problem of egomotion estimation is taken, based on constraints of a global nature. It is proved that local normal flow measurements form global patterns in the image plane. The position of these patterns is related to the three dimensional motion parameters. By locating some of these patterns, which depend only on subsets of the motion parameters, through a simple search technique, the 3-D motion parameters can be found. The proposed algorithmic procedure is very robust, since it is not affected by small perturbations in the normal flow measurements. As a matter of fact, since only the sign of the normal flow measurement is employed, the direction of translation and the axis of rotation can be estimated with up to 100% error in the image measurements.< >

关键词： Motion estimation computer vision Automation image motion analysis Fluid flow measurement Motion measurement Rotation measurement Laboratories Educational institutions Geometrical optics

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

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) 2013年 7877 LNCS卷 VI页

作者： Kropatsch, Walter G. Artner, Nicole M. Haxhimusa, Yll Jiang, Xiaoyi Vienna University of Technology Department of Pattern Recognition and Image Processing Favoritenstr. 9-11 186-3 1040 Vienna Austria University of Münster Department of Computer Science Einsteinstr. 62 48149 Münster Germany

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Mobile robot localization under varying illumination

Mobile robot localization under varying illumination

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International Conference on pattern recognition

作者： M. Jogan A. Leonardis H. Wildenauer H. Bischof Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Pattern Recognition and Image Processing Group Institute for Computer Aided Automation University of Technology Vienna Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria

Methods for mobile robot localization that use eigenspaces of panoramic snapshots of the environment are in general sensitive to changes in the illumination of the environment. Therefore, we propose an approach which achieves a reliable localization under severe illumination conditions. The method uses gradient filtering of the eigenspace. After testing the approach on images obtained by a mobile robot, we show that it outperforms the standard eigenspace-based recognition method.

关键词： Mobile robots Lighting computer vision Filter bank image recognition Indoor environments pattern recognition image processing computer graphics Information science

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An efficient and scalable learning algorithm for Near-Earth objects detection in astronomy big image data

An efficient and scalable learning algorithm for Near-Earth ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ke Wang Ping Guo School of computer Science and Technology Beijing Institute of Technology Beijing P.R. China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing P.R. China

ISBN: (纸本)9781479938414

In this paper, we investigate the efficiency and scalability of Gaussian mixture model based learning algorithm for the detection of Near-Earth objects in large scale astronomy image data. We propose an effective scheme to reduce the computational complexity of current learning algorithm, this is achieved by adopting the perceptual image hashing method. Our proposed scheme is validated on raw astronomy image data. The experiment results illustrate that both efficiency and scalability are improved significantly in astronomical scenario and other scenario.

关键词： Astronomy Scalability Big data Data mining Gaussian distribution Hamming distance Gaussian mixture model

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Learning distance transform for boundary detection and deformable segmentation in CT prostate images

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) 2014年 8679卷 93-100页

作者： Gao, Yaozong Wang, Li Shao, Yeqin Shen, Dinggang Department of Radiology and BRIC University of North Carolina at Chapel Hill United States Department of Computer Science University of North Carolina at Chapel Hill United States Institution of Image Processing & Pattern Recognition Shanghai Jiao Tong University China

Segmenting the prostate from CT images is a critical step in the radiotherapy planning for prostate cancer. The segmentation accuracy could largely affect the efficacy of radiation treatment. However, due to the touching boundaries with the bladder and the rectum, the prostate boundary is often ambiguous and hard to recognize, which leads to inconsistent manual delineations across different clinicians. In this paper, we propose a learning-based approach for boundary detection and deformable segmentation of the prostate. Our proposed method aims to learn a boundary distance transform, which maps an intensity image into a boundary distance map. To enforce the spatial consistency on the learned distance transform, we combine our approach with the auto-context model for teratively refining the estimated distance map. After the refinement, the prostate boundaries can be readily detected by finding the valley in the distance map. In addition, the estimated distance map can also be used as a new external force for guiding the deformable segmentation. Specifically, to automatically segment the prostate, we integrate the estimated boundary distance map into a level set formulation. Experimental results on 73 CT planning images show that the proposed distance transform is more effective than the traditional classification-based method for driving the deformable segmentation. Also, our method can achieve more consistentsegmentations than human raters, and more accurate results than the existing methods under comparison. © Springer International Publishing Switzerland 2014.

关键词： computerized tomography

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