Texture Analysis In Machine Vision

Author : M K Pietikäinen
Publisher : World Scientific
Page : 280 pages
File Size : 52,6 Mb
Release : 2000-10-13
Category : Computers
ISBN : 9789814492683

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Texture Analysis in Machine Vision by M K Pietikäinen Pdf

Texture analysis is an important generic research area of machine vision. The potential areas of application include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, content-based retrieval from image databases, document analysis, biometric person authentication, scene analysis for robot navigation, texture synthesis for computer graphics and animation, and image coding. Texture analysis has been a topic of intensive research for over three decades, but the progress has been very slow. A workshop on “Texture Analysis in Machine Vision” was held at the University of Oulu, Finland, in 1999, providing a forum for presenting recent research results and for discussing how to make progress in order to increase the usefulness of texture in practical applications. This book contains extended and revised versions of the papers presented at the workshop. The first part of the book deals with texture analysis methodology, while the second part covers various applications. The book gives a unique view of different approaches and applications of texture analysis. It should be of great interest both to researchers of machine vision and to practitioners in various application areas. Contents:Nonparametric Texture Analysis with Complementary Spatial Operators (M Pietikäinen & T Ojala)Multi-Resolution Clustering of Texture Images (S Battiato & G Gallo)Robustness of Local Binary Pattern (LBP) Operators to Tilt-Compensated Textures (M Soriano et al.)Using Texture in Image Similarity and Retrieval (S Aksoy & R M Haralick)Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine (P C Yuen et al.)Feature Evaluation of Texture Test Objects for Magnetic Resonance Imaging (A Materka et al.)Automatic Detection of Errors on Textures Using Invariant Grey-Scale Features and Polynomial Classifiers (M Schael & H Burkhardt)Combining Analysis and Synthesis of Textures for the Animation Industry (M Ollila et al.)and other papers Readership: Researchers, graduate students and industrialists in the field of machine vision. Keywords:Computer Vision;Image Analysis;Pattern Recognition;Feature Extraction;Classification;Segmentation;Texture Synthesis;Surface Properties;Color Texture;Applications

Author : Majid Mirmehdi,Xianghua Xie,Jasjit S. Suri
Publisher : World Scientific
Page : 424 pages
File Size : 55,6 Mb
Release : 2008
Category : Computers
ISBN : 9781848161153

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Handbook of Texture Analysis by Majid Mirmehdi,Xianghua Xie,Jasjit S. Suri Pdf

Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be used alone or in combination with other sensed features (e.g. color, shape, or motion) to perform the task of recognition. Either way, it is a feature of paramount importance and boasts a tremendous body of work in terms of both research and applications.Currently, the main approaches to texture analysis must be sought out through a variety of research papers. This collection of chapters brings together in one handy volume the major topics of importance, and categorizes the various techniques into comprehensible concepts. The methods covered will not only be relevant to those working in computer vision, but will also be of benefit to the computer graphics, psychophysics, and pattern recognition communities, academic or industrial.

Author : Chih-Cheng Hung,Enmin Song,Yihua Lan
Publisher : Springer
Page : 264 pages
File Size : 52,9 Mb
Release : 2019-06-05
Category : Computers
ISBN : 9783030137731

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Image Texture Analysis by Chih-Cheng Hung,Enmin Song,Yihua Lan Pdf

This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis. Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks. This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.

Author : Matti Pietik„inen
Publisher : World Scientific
Page : 284 pages
File Size : 47,7 Mb
Release : 2000
Category : Computers
ISBN : 9810243731

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Texture Analysis in Machine Vision by Matti Pietik„inen Pdf

d104ure analysis is an important generic research area of machine vision. The potential areas of application include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, content-based retrieval from image databases, document analysis, biometric person authentication, scene analysis for robot navigation, texture synthesis for computer graphics and animation, and image coding. d104ure analysis has been a topic of intensive research for over three decades, but the progress has been very slow.A workshop on ?d104ure Analysis in Machine Vision? was held at the University of Oulu, Finland, in 1999, providing a forum for presenting recent research results and for discussing how to make progress in order to increase the usefulness of texture in practical applications. This book contains extended and revised versions of the papers presented at the workshop. The first part of the book deals with texture analysis methodology, while the second part covers various applications. The book gives a unique view of different approaches and applications of texture analysis. It should be of great interest both to researchers of machine vision and to practitioners in various application areas.

Author : Fumiaki Tomita,Saburo Tsuji
Publisher : Springer Science & Business Media
Page : 179 pages
File Size : 43,6 Mb
Release : 2013-11-11
Category : Computers
ISBN : 9781461315537

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Computer Analysis of Visual Textures by Fumiaki Tomita,Saburo Tsuji Pdf

This book presents theories and techniques for perception of textures by computer. Texture is a homogeneous visual pattern that we perceive in surfaces of objects such as textiles, tree barks or stones. Texture analysis is one of the first important steps in computer vision since texture provides important cues to recognize real-world objects. A major part of the book is devoted to two-dimensional analysis of texture patterns by extracting statistical and structural features. It also deals with the shape-from-texture problem which addresses recovery of the three-dimensional surface shapes based on the geometry of projection of the surface texture to the image plane. Perception is still largely mysterious. Realizing a computer vision system that can work in the real world requires more research and ex periment. Capability of textural perception is a key component. We hope this book will contribute to the advancement of computer vision toward robust, useful systems. vVe would like to express our appreciation to Professor Takeo Kanade at Carnegie Mellon University for his encouragement and help in writing this book; to the members of Computer Vision Section at Electrotechni cal Laboratory for providing an excellent research environment; and to Carl W. Harris at Kluwer Academic Publishers for his help in preparing the manuscript.

Author : Chi Hau Chen,Louis-francois Pau,Patrick S P Wang
Publisher : World Scientific
Page : 1045 pages
File Size : 47,6 Mb
Release : 1999-03-12
Category : Computers
ISBN : 9789814497640

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Handbook Of Pattern Recognition And Computer Vision (2nd Edition) by Chi Hau Chen,Louis-francois Pau,Patrick S P Wang Pdf

The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.

Author : Fumiaki Tomita,Saburo Tsuji
Publisher : Springer
Page : 173 pages
File Size : 50,8 Mb
Release : 2013-08-21
Category : Computers
ISBN : 1461315549

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Computer Analysis of Visual Textures by Fumiaki Tomita,Saburo Tsuji Pdf

This book presents theories and techniques for perception of textures by computer. Texture is a homogeneous visual pattern that we perceive in surfaces of objects such as textiles, tree barks or stones. Texture analysis is one of the first important steps in computer vision since texture provides important cues to recognize real-world objects. A major part of the book is devoted to two-dimensional analysis of texture patterns by extracting statistical and structural features. It also deals with the shape-from-texture problem which addresses recovery of the three-dimensional surface shapes based on the geometry of projection of the surface texture to the image plane. Perception is still largely mysterious. Realizing a computer vision system that can work in the real world requires more research and ex periment. Capability of textural perception is a key component. We hope this book will contribute to the advancement of computer vision toward robust, useful systems. vVe would like to express our appreciation to Professor Takeo Kanade at Carnegie Mellon University for his encouragement and help in writing this book; to the members of Computer Vision Section at Electrotechni cal Laboratory for providing an excellent research environment; and to Carl W. Harris at Kluwer Academic Publishers for his help in preparing the manuscript.

Author : Jyotismita Chaki,Nilanjan Dey
Publisher : Springer Nature
Page : 100 pages
File Size : 41,9 Mb
Release : 2019-10-24
Category : Technology & Engineering
ISBN : 9789811508530

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Texture Feature Extraction Techniques for Image Recognition by Jyotismita Chaki,Nilanjan Dey Pdf

The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based. It also covers applications related to texture features, such as facial imaging. It is a valuable resource for machine vision researchers and practitioners in different application areas.

Author : Nanning Zheng,Xiaoyi Jiang,Xuguang Lan
Publisher : Springer
Page : 514 pages
File Size : 48,5 Mb
Release : 2006-08-15
Category : Computers
ISBN : 9783540375982

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Advances in Machine Vision, Image Processing, and Pattern Analysis by Nanning Zheng,Xiaoyi Jiang,Xuguang Lan Pdf

This book collects the proceedings of the International Workshop on Intelligent Computing in Pattern Analysis/Synthesis, IWICPAS 2006, held in Xi'an, China alongside the 18th International Conference on Pattern Recognition, ICPR 2006. The book presents 51 revised full papers and 128 revised poster papers, organized in topical sections on object detection, tracking and recognition, pattern representation and modeling, visual pattern modeling, image processing, compression and coding and texture analysis/synthesis.

Author : Matti Pietikäinen,Abdenour Hadid,Guoying Zhao,Timo Ahonen
Publisher : Springer Science & Business Media
Page : 212 pages
File Size : 43,6 Mb
Release : 2011-06-21
Category : Mathematics
ISBN : 9780857297488

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Computer Vision Using Local Binary Patterns by Matti Pietikäinen,Abdenour Hadid,Guoying Zhao,Timo Ahonen Pdf

The recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have provided outstanding results in problems relating to face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: local binary patterns and their variants in spatial and spatiotemporal domains, texture classification and segmentation, description of interest regions, applications in image retrieval and 3D recognition - Recognition and segmentation of dynamic textures, background subtraction, recognition of actions, face analysis using still images and image sequences, visual speech recognition and LBP in various applications. Written by pioneers of LBP, this book is an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will also be of interest to all those who work with specific applications of machine vision.

Author : Milan Sonka,Vaclav Hlavac,Roger Boyle
Publisher : Springer
Page : 579 pages
File Size : 50,5 Mb
Release : 2013-11-11
Category : Computers
ISBN : 9781489932167

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Image Processing, Analysis and Machine Vision by Milan Sonka,Vaclav Hlavac,Roger Boyle Pdf

Image Processing, Analysis and Machine Vision represent an exciting part of modern cognitive and computer science. Following an explosion of inter est during the Seventies, the Eighties were characterized by the maturing of the field and the significant growth of active applications; Remote Sensing, Technical Diagnostics, Autonomous Vehicle Guidance and Medical Imaging are the most rapidly developing areas. This progress can be seen in an in creasing number of software and hardware products on the market as well as in a number of digital image processing and machine vision courses offered at universities world-wide. There are many texts available in the areas we cover - most (indeed, all of which we know) are referenced somewhere in this book. The subject suffers, however, from a shortage of texts at the 'elementary' level - that appropriate for undergraduates beginning or completing their studies of the topic, or for Master's students - and the very rapid developments that have taken and are still taking place, which quickly age some of the very good text books produced over the last decade or so. This book reflects the authors' experience in teaching one and two semester undergraduate and graduate courses in Digital Image Processing, Digital Image Analysis, Machine Vision, Pattern Recognition and Intelligent Robotics at their respective institutions.

Author : C. H. Chen,L -F. Pau,Patrick S. P. Wang
Publisher : World Scientific
Page : 1045 pages
File Size : 54,7 Mb
Release : 1999
Category : Computers
ISBN : 9789812384737

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Handbook of Pattern Recognition and Computer Vision by C. H. Chen,L -F. Pau,Patrick S. P. Wang Pdf

The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.

Author : Milan Hájek
Publisher : Texture Analysis Magn Resona
Page : 248 pages
File Size : 43,6 Mb
Release : 2006
Category : Magnetic resonance imaging
ISBN : 8090366007

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Texture Analysis for Magnetic Resonance Imaging by Milan Hájek Pdf

Author : Fabio Solari,Manuela Chessa,Silvio P. Sabatini
Publisher : BoD – Books on Demand
Page : 288 pages
File Size : 44,7 Mb
Release : 2012-03-23
Category : Technology & Engineering
ISBN : 9789535103738

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Machine Vision by Fabio Solari,Manuela Chessa,Silvio P. Sabatini Pdf

Vision plays a fundamental role for living beings by allowing them to interact with the environment in an effective and efficient way. The ultimate goal of Machine Vision is to endow artificial systems with adequate capabilities to cope with not a priori predetermined situations. To this end, we have to take into account the computing constraints of the hosting architectures and the specifications of the tasks to be accomplished, to continuously adapt and optimize the visual processing techniques. Nevertheless, by exploiting the low?cost computational power of off?the?shell computing devices, Machine Vision is not limited any more to industrial environments, where situations and tasks are simplified and very specific, but it is now pervasive to support system solutions of everyday life problems.

Author : Tapan K. Gandhi,Siddhartha Bhattacharyya,Sourav De,Debanjan Konar,Sandip Dey
Publisher : Academic Press
Page : 308 pages
File Size : 49,5 Mb
Release : 2020-08-11
Category : Computers
ISBN : 9780128192962

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Advanced Machine Vision Paradigms for Medical Image Analysis by Tapan K. Gandhi,Siddhartha Bhattacharyya,Sourav De,Debanjan Konar,Sandip Dey Pdf

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis