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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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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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Implicitly Constrained Semi-supervised Linear Discriminant Analysis

Implicitly Constrained Semi-supervised Linear Discriminant A...

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International Conference on pattern recognition

作者： Jesse H. Krijthe Marco Loog Department of Molecular Epidemiology Leiden University Medical Center The Netherlands Pattern Recognition Laboratory Delft University of Technology The Netherlands The Image Group Department of Computer Science University of Copenhagen Denmark

ISBN: (纸本)9781479952106

Semi-supervised learning is an important and active topic of research in pattern recognition. For classification using linear discriminant analysis specifically, several semi-supervised variants have been proposed. Using any one of these methods is not guaranteed to outperform the supervised classifier which does not take the additional unlabeled data into account. In this work we compare traditional Expectation Maximization type approaches for semi-supervised linear discriminant analysis with approaches based on intrinsic constraints and propose a new principled approach for semi-supervised linear discriminant analysis, using so-called implicit constraints. We explore the relationships between these methods and consider the question if and in what sense we can expect improvement in performance over the supervised procedure. The constraint based approaches are more robust to misspecification of the model, and may outperform alternatives that make more assumptions on the data in terms of the log-likelihood of unseen objects.

关键词： Linear discriminant analysis Covariance matrices Mathematical model Semisupervised learning Equations Labeling pattern recognition

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Modeling multisource remote sensing image classifier based on the MDL principle: Theoretical aspects

Modeling multisource remote sensing image classifier based o...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qian Yin Ping Guo Zhi-Yong Yuan Zu-Kuan Wei Wen-Yi Zeng Image Processing & Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science Wuhan University of China Wuhan China School of Comp. Science & Engr. University of Electronic Science and Technology Chengdu China

A theoretical study for modeling technique of the remote sensing image classification based on the minimum description length (MDL) principle is presented in the paper. According to the MDL principle, modeling problem is an optimization procedure to find the shortest expected code length. Kullback-Leibler (KL) divergence is adopted as the system cost function to measure expected codelength, and the codelength will be the model we desired. The advantage of using the MDL principle to build appropriate model is analyzed theoretically, model optimization technique also is described.

关键词： Data models Remote sensing Mathematical model Classification algorithms Computational modeling Equations Artificial neural networks

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Impulse noise removal using linear prediction model

Impulse noise removal using linear prediction model

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4th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, ITELSIKS 1999

作者： Prudyus, Ivan Voloshynovskiy, Sviatoslav Rytsar, Yuriy Holotyak, Taras Radio Engineering Faculty State University Lvivska Polytechnika 12 S.Bandery Str. Lviv 290646 Ukraine Coordinated Science Laboratory University of Illinois College of Engineering 1308 West Main Street Urbana IL 61801-2307 United States Department of Image Processing and Pattern Recognition Institute of Physics and Mechanics National Academy of Science of Ukraine 5 Naukova str. Lviv Ukraine

ISBN: (纸本)078035768X

Noise removal is an important problem in many applications. In this paper a new two-step scheme of the decision-based impulse noise removal method by means of contaminated pixel detection is proposed and comparison with direct order statistic filtering is given. The proposed methods satisfy both objective and subjective image quality. © 1999 IEEE.

关键词： Impulse noise

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Preface [Special issue intro.]

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IEEE Transactions on pattern Analysis and Machine Intelligence 1979年第2期PAMI-1卷 125-126页

作者： Y. T. Chien Theodosios Pavlidis Guest Editor Professor and Head of the Department of Electrical Engineering and Computer Science. Guest Editor member of the Association for Computing Machinery and Sigma Xi member of the editorial committee of the IEEE TRANSACTIONS OF PATTERN ANALYSIS AND MACHINE INTELLIGENCE Associate Editor of the Bulletin of Mathematical Biology Computer Graphics and Image Processing and Pattern Recognition.

This Special Issue is composed of the papers selected from the 1978 IEEE computer Society Workshop on pattern recognition (PR) and Artificial Intelligence (Al) held in Princeton, NJ, April 12-14, 1978. The Workshop was sponsored by the Technical Committee on Machine Intelligence and pattern Analysis. Inevitably, the contributors to the Workshop determined, to a large degree, the tone and complexion of this Special Issue. For this reason, a brief account of the Workshop Proceedings, though now history, is given. About half of the papers presented at the Workshop were also submitted for the Special Issue, a total of 37. Those of high quality were far more than the number that could be accommodated within the available number of pages. We decided to choose three topics where the interaction between the methodologies of PR and Al was most prevelant: analysis of images, analysis of speech, and certain general algorithms. All the selected papers present either theoretical, or experimental results, or both. We felt that such results clearly demonstrate the progress achieved and can be seen as very impressive if measured against the difficult problem of emulating functions associated with human intelligence by machines. It is true that they often fall short from some of the earlier ambitious goals, but the time is probably ripe to reexamine such goals in view of the accumulated experience. The following is a brief scanning of the contents of this issue, especially as related to the integration and/or interaction of PR and Al methodologies.

关键词： Artificial intelligence pattern recognition image analysis Speech analysis Conferences Labeling Machine intelligence Algorithm design and analysis image edge detection computer Society

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DSA image registration based on multiscale Gabor filters and mutual information

DSA image registration based on multiscale Gabor filters and...

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International Conference on Information and Automation (ICIA)

作者： Zhiguo Cao Xiaoxiao Liu Bo Peng Yiu-Sang Moon Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science and Engineering Chinese University of Hong Kong New Territories Hong Kong China

In clinical practice, digital subtraction angiography (DSA) is a powerful technique for the visualization of blood vessels in X-ray image sequences. Different with traditional DSA image registration processes, in our proposed image registration method, the control points are selected from the vessel centerlines using multiscale Gabor filters, and mutual information (MI) is then taken as the similarity criterion to find the correspondences. Experimental results demonstrate our algorithm efficiently yields satisfying registration result for DSA images.

关键词： image registration Gabor filters Mutual information Biomedical imaging Angiography Visualization Displacement control Blood vessels image sequences Pixel

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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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Robust real-time tracking for visual surveillance

Eurasip Journal on Advances in Signal Processing

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Eurasip Journal on Advances in Signal processing 2007年 2007卷

作者： Thirde, David Borg, Mark Aguilera, Josep Wildenauer, Horst Ferryman, James Kampel, Martin School of Systems Engineering Computational Vision Group University of Reading Reading RG6 6AY United Kingdom Computer Science Department Pattern Recognition and Image Processing Group Vienna University of Technology Vienna 1040 Austria

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii)object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright © 2007 Hindawi Publishing Corporation. All rights reserved.

关键词： Tracking (position)

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Preliminary Design of a Terrain recognition System

Preliminary Design of a Terrain Recognition System

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Fan Zhang Zheng Fang Ming Liu He Huang department of Electrical Computer and Biomedical Engineering University of Rhode Island National Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

ISBN: (纸本)9781424441211

This paper aims to design a wearable terrain recognition system, which might assist the control of powered artificial prosthetic legs. A laser distance sensor and inertial measurement unit (IMU) sensors were mounted on human body. These sensors were used to identify the movement state of the user, reconstruct the geometry of the terrain in front of the user while walking, and recognize the type of terrain before the user stepped on it. Different sensor configurations were investigated and compared. The designed system was evaluated on one healthy human subject when walking on an obstacle course in the laboratory environment. The results showed that the reconstructed terrain height demonstrated clearer pattern difference among studied terrains when the laser was placed on the waist than that when the laser was mounted on the shank. The designed system with the laser on the waist accurately recognized 157 out of 160 tested terrain transitions, 300ms-2870ms before the user switched the negotiated terrains. These promising results demonstrated the potential application of the designed terrain recognition system to further improve the control of powered artificial legs.

关键词： terrains preliminary design landscapes recognition system Laser design system Consumers Waist range sensor laboratory environment human subject walking

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