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Document segmentation using texture analysis

Document segmentation using texture analysis

引用

international conference on pattern recognition

作者： J.S. Payne T.J. Stonham D. Patel Department of Computing Buckinghamshire College Brunel University High Wycombe Buckinghamshire UK Department of Electrical Engineering Brunel University High Wycombe Uxbridge UK

this paper describes the application of a novel texture recognition strategy, which involves the assembly of n/sup th/ order co-occurrence information within a processing window. the resulting spectrum is processed by a nearest neighbour classifier, and discontinuities in the classification as the operating window scans the image are recognized as texture boundaries. the technique is being applied for the first time to segmenting newsprint, in order to locate the text regions for effective data capture. Previous methods applied to the task discussed in the paper, have used run-length encoding and block analysis, Gabor filters, or component analysis. the co-occurrence method offers significant advantages in processing time and ease of implementation.

关键词： Gabor filters Image segmentation Optical character recognition software Image analysis Image texture analysis Pixel Material storage Image coding Fourier transforms Educational institutions

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Components analysis of hidden Markov models in computer vision

Components analysis of hidden Markov models in computer visi...

引用

international conference on Image Analysis and Processing

作者： T. Caelli B. McCane Department of Computing Science University of Algarve Edmonton AB Canada University of Otago Dunedin New Zealand

Hidden Markov models (HMMs) have become a standard tool for pattern recognition in computer vision. Although parameter and topology estimation have been studied, and still are, detailed analysis of how these estimated parameters contribute to HMM performance is rarely addressed. We develop tools for measuring such contributions and illustrate key issues in a representative task of gesture recognition - 3D motion recovery from 2D projections.

关键词： Hidden Markov models Computer vision Image analysis

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Modeling of some spatio-temporal aspects of visual information processing in the retinal neural network

Modeling of some spatio-temporal aspects of visual informati...

引用

international conference on pattern recognition

作者： A. Faure N. Shevtsova A. Golovan A. Klepach O. Cachard I. Rybak Laboratory Logos University of Le Havre France AB Kogan Research Institute for Neurocybernetics Rostov State University Rostov on Donu Russia University of Pennsylvania Philadelphia PA USA

the problems of active vision and of visual perception and recognition in the dynamic environment demand a very careful consideration of dynamic aspects of early visual processing. In the first turn it concerns the finding out the relationships between the dynamic properties of sensory processing elements (retinal neurons), velocities of movements of elements of the visible world, and general structure of the retinal receptive fields. In this work we have tried to consider the above issues using a very simple model of the retinal neural network.

关键词： Information processing Retina Neural networks Image resolution Neurons Visual perception Intelligent networks Eyes Biology computing Computer vision

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Rough set year in India 2009 1

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12th international conference on Rough Sets, Fuzzy Sets, Data Mining and Granular computing, RSFDGrC 2009

作者： Joshi, Manish Bhaumik, Rabi N. Lingras, Pawan Patil, Nitin Salgaonkar, Ambuja Ślȩzak, Dominik Department of Computer Science North Maharashtra University Jalgaon Maharashtra 425 001 India Department of Mathematics Tripura University Suryamaninagar Tripura 799 130 India Department of Mathematics and Computing Science Saint Mary's University Halifax NS B3H 3C3 Canada Department of Computer Science University of Pune Pune 411 007 India Department of Computer Science University of Mumbai Mumbai 400 098 India Institute of Mathematics University of Warsaw Banacha 2 Warsaw 02-097 Poland Infobright Inc. Poland Krzywickiego 34 pok. 219 Warsaw 02-078 Poland

ISBN: (数字)9783642106460

ISBN: (纸本)3642106455

Since its inception in early 80's, the rough set theory has attracted a lot of interest from global research community. It turns out as useful in building classification and prediction models. It complements a number of other soft computing paradigms. It may be combined with fuzzy logic and probabilistic data analysis. It has led towards enhancements of neural networks, genetic algorithms, clustering, support vector machines, regressionmodels, et cetera. Its application domains include pattern recognition, feature selection, information retrieval, bioinformatics, computer vision, multimedia, medicine, retail data mining, web mining, control, traffic engineering, data warehousing, and many others. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Rough set theory

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Transactions on Rough Sets XIV 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： James F. Peters Andrzej Skowron Dominik Slezak Hiroshi Sakai Mihir Kumar Chakraborty Aboul Ella Hassanien William Zhu

ISBN: (数字)9783642215636

ISBN: (纸本)9783642215629

the LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XIV contains 11 revised extended papers from the 12th international conference on Rough Sets, Fuzzy Sets, Data Mining and Granular computing, RSFDGrC 2009, held in Delhi, India. the topics include various rough set generalizations in combination with formal concept analysis, lattice theory, fuzzy sets and belief functions, rough and fuzzy clustering techniques, as well as applications to gene selection, web page recommendation systems, facial recognition, and temporal pattern detection. in addition, this volume contains a regular article on rough multiset and its multiset topology.

关键词： Mathematical Logic and Formal Languages Computation by Abstract Devices theory of Computation Image Processing and Computer Vision pattern recognition Artificial Intelligence

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ISR3: communication and data storage for an unmanned ground vehicle

ISR3: communication and data storage for an unmanned ground ...

引用

international conference on pattern recognition

作者： B.A. Draper G. Kutlu E.M. Riseman A.R. Hanson Computer Vision Laboratory Department of Computer Science University of Massachusetts Amherst MA USA University of Massachusetts Amherst Amherst MA US

Computer vision researchers working in mobile robotics and other real-time domains are forced to confront issues not normally addressed in the computer vision literature. Among these are: communications or how to get data from one process to another; data storage and retrieval (primarily for transient image-based data); and database management for maps, object model and other permanent (typically 3D) data. this paper reviews efforts at CMU, SRI and UMass to build real-time computer vision systems for mobile robotics, and presents a new tool, called ISR3, for communications, data storage/retrieval and database management on the UMass Mobile Perception Laboratory (MPL), a NAVLAB-like autonomous vehicle.

关键词： Memory Land vehicles Mobile communication Computer vision Mobile computing Mobile robots Robot vision systems Information retrieval Image databases Image retrieval

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Physics-based object pose and shape estimation from multiple views

Physics-based object pose and shape estimation from multiple...

引用

international conference on pattern recognition

作者： M. Chan D. Metaxas Department of Computer and Information Science University of Pennsylvania Philadelphia PA USA

this paper presents a new algorithm for object pose and shape estimation from multiple views. Using a qualitative shape recovery scheme the authors first segment the image into parts which belong to a vocabulary of primitives. Based on the additional constraints provided by the qualitative shapes the authors extend their physics-based framework to allow object pose and shape estimation from stereo images where the two cameras have arbitrary relative orientations. the authors then generalize their algorithm to integrate measurements from multiple views. To recover more complex objects the authors generalize the definition for the global bending deformation. the authors also present an algorithm for model discretization which evenly tessellates the model surface. the authors demonstrate the usefulness of their technique in experiments involving real images from of a variety of object shapes which may be partially occluded.

关键词： Shape Deformable models Image segmentation Cameras Physics computing Information science Vocabulary Data mining Noise robustness Noise shaping

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Estimating 3D motion and shape of multiple objects using Hough transform

Estimating 3D motion and shape of multiple objects using Hou...

引用

international conference on pattern recognition

作者： Tina Yu Tian M. Shah Computer Vision Lab Computer Science Department University of Central Florida Orlando FL USA

Presents a robust method to determine 3D motion and structure of multiple objects. Rather than segmenting the scene containing multiple motions using 3D parametric model, the authors use the general 3D motion model and exploit Hough transform and robust estimation techniques to determine motion and segmentation simultaneously for an arbitrary scene. the authors divide the input image into patches, and for each sample of the translation space and each patch, the authors compute the rotation parameters using weighted least-squares fit. Each patch votes for a sample in the five-dimensional parameter space (translation and rotation). the multiple local maxima in the parameter space naturally correspond to the multiple moving objects. the authors' experimental results show that the proposed method is robust and relatively insensitive to noise.

关键词： Motion estimation Shape Image motion analysis Layout Computer vision Image segmentation Parametric statistics Noise robustness Optical noise Optical computing

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Computational Intelligence in Data Science 1

引用

丛书名： IFIP Advances in Information and Communication Technology

1000年

作者： Sarath Chandran K R Sujaudeen N Beulah A Shahul Hamead H

ISBN: (数字)9783031382963

ISBN: (纸本)9783031382956;9783031384103

this book constitutes the proceedings of the 6th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2023, which took place in Kalavakkam, India, in February 2023.;the 24 full papers presented in this volume were carefully reviewed and selected from 134 submissions. the major theme of the conference was intended to be computation intelligence and knowledge management. Various emerging areas like IoT, cyber security and data science need computation intelligence to align with the cutting-edge research. Machine learning delivers insights hidden in data for rapid, automated responses and improved decision making. Machine learning for IoT can be used to project future trends, detect anomalies, and augment intelligence by ingesting image, video, and audio.

关键词： Data Mining and Knowledge Discovery Computer Applications Artificial Intelligence Computer Imaging, Vision, pattern recognition and Graphics computing Milieux

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A VLSI implementation of a parallel, self-organizing learning model

A VLSI implementation of a parallel, self-organizing learnin...

引用

international conference on pattern recognition

作者： M.G. Stout L.G. Salmon G.L. Rudolph T.R. Martinez Department of Electrical and Computer Engineering Brigham Young University Provo UT USA Department of Computer Science Brigham Young University Provo UT USA

this paper presents a VLSI implementation of the priority adaptive self-organizing concurrent system (PASOCS) learning model that is built using a multichip module (MCM) substrate. Many current hardware implementations of neural network learning models are direct implementations of classical neural network structures-a large number of simple computing nodes connected by a dense number of weighted links. PASOCS is one of a class of ASOCS (adaptive self-organizing concurrent system) connectionist models whose overall goal is the same as classical neural networks models, but whose functional mechanisms differ significantly. this model has potential application in areas such as pattern recognition, robotics, logical inference, and dynamic control.

关键词： Very large scale integration Neural networks Logic Computer networks pattern recognition Network topology Circuit simulation Discrete event simulation Binary search trees Adaptive systems

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