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Handbook of Texture Analysis

Author: Majid Mirmehdi

Publisher: World Scientific

Published: 2008

Total Pages: 424

ISBN-13: 1848161158

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.

Handbook of Pattern Recognition and Computer Vision

Author: C. H. Chen

Publisher: World Scientific

Published: 1999

Total Pages: 1045

ISBN-13: 9812384731

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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.

Handbook of Texture Analysis

Author: Ayman El-Baz

Publisher: CRC Press

Published: 2024-06-24

Total Pages: 262

ISBN-13: 1040008984

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The major goals of texture research in computer vision are to understand, model, and process texture, and ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This book examines four major application domains related to texture analysis and their relationship to AI-based industrial applications: texture classification, texture segmentation, shape from texture, and texture synthesis. This volume: Discusses texture-based segmentation for extracting image shape features, modeling and segmentation of noisy and textured images, spatially constrained color-texture model for image segmentation, and texture segmentation using Gabor filters Examines textural features for image classification, a statistical approach for classification, texture classification from random features, and applications of texture classifications Describes shape from texture, including general principles, 3D shapes, and equations for recovering shape from texture Surveys texture modeling, including extraction based on Hough transformation and cycle detection, image quilting, gray level run lengths, and use of Markov random fields Aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering, this is an essential reference for those looking to advance their understanding in this applied and emergent field.

Handbook of Texture Analysis

Author: Ayman El-Baz

Publisher:

Published: 2024-04-25

Total Pages: 0

ISBN-13: 9780367483456

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This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis.

Introduction to Texture Analysis

Author: Olaf Engler

Publisher: CRC Press

Published: 2009-11-16

Total Pages: 490

ISBN-13: 1420063669

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The first edition of Introduction to Texture Analysis: Macrotexture, Microtexture, and Orientation Mapping broke new ground by collating seventy years worth of research in a convenient single-source format. Reflecting emerging methods and the evolution of the field, the second edition continues to provide comprehensive coverage of the concepts, pra

Image Texture Analysis

Author: Chih-Cheng Hung

Publisher: Springer

Published: 2019-06-05

Total Pages: 264

ISBN-13: 3030137732

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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.

Handbook of Image Processing and Computer Vision

Author: Arcangelo Distante

Publisher: Springer Nature

Published: 2020-05-28

Total Pages: 507

ISBN-13: 303038148X

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Across three volumes, the Handbook of Image Processing and Computer Vision presents a comprehensive review of the full range of topics that comprise the field of computer vision, from the acquisition of signals and formation of images, to learning techniques for scene understanding. The authoritative insights presented within cover all aspects of the sensory subsystem required by an intelligent system to perceive the environment and act autonomously. Volume 1 (From Energy to Image) examines the formation, properties, and enhancement of a digital image. Topics and features: • Describes the fundamental processes in the field of artificial vision that enable the formation of digital images from light energy • Covers light propagation, color perception, optical systems, and the analog-to-digital conversion of the signal • Discusses the information recorded in a digital image, and the image processing algorithms that can improve the visual qualities of the image • Reviews boundary extraction algorithms, key linear and geometric transformations, and techniques for image restoration • Presents a selection of different image segmentation algorithms, and of widely-used algorithms for the automatic detection of points of interest • Examines important algorithms for object recognition, texture analysis, 3D reconstruction, motion analysis, and camera calibration • Provides an introduction to four significant types of neural network, namely RBF, SOM, Hopfield, and deep neural networks This all-encompassing survey offers a complete reference for all students, researchers, and practitioners involved in developing intelligent machine vision systems. The work is also an invaluable resource for professionals within the IT/software and electronics industries involved in machine vision, imaging, and artificial intelligence. Dr. Cosimo Distante is a Research Scientist in Computer Vision and Pattern Recognition in the Institute of Applied Sciences and Intelligent Systems (ISAI) at the Italian National Research Council (CNR). Dr. Arcangelo Distante is a researcher and the former Director of the Institute of Intelligent Systems for Automation (ISSIA) at the CNR. His research interests are in the fields of Computer Vision, Pattern Recognition, Machine Learning, and Neural Computation.

Handbook of Texture Analysis

Author: Ayman El-Baz

Publisher:

Published: 2024-04

Total Pages: 0

ISBN-13: 9781032727417

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This two-volume handbook provides a comprehensive view of texture analysis in both AI-based industrial and medical imaging applications. The first volume covers texture analysis for neuroradiology; information-theoretic entropy; chronic liver diseases; clinical management of focal liver lesions; abdominal imaging; optical coherence tomography images; thoracic imaging; prostate cancer; breast cancer; bladder cancer, quality evaluation of meat products; and detection of powdery mildew on strawberry leaves. The second volume covers Local Binary Descriptors for Texture Classification; Precision Grading of Glioma; Liver Tumor Detection and Grading; Texture Analysis in Radiology; Texture Analysis Using a Self-Organizing Feature Map; Sensor-Based Human Activity Recognition Analysis Using Machine Learning and Topological Data Analysis; Texture Analysis in Retinal OCT Imaging; Pneumonia Detection; Prostatic Adenocarcinoma; and Texture Analysis in Cancer Prognosis. Aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering, this handbook is an essential reference for those looking to advance their understanding in this applied and emergent field.

Food Texture Design and Optimization

Author: Yadunandan Lal Dar

Publisher: John Wiley & Sons

Published: 2014-05-27

Total Pages: 464

ISBN-13: 0470672420

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Food texture has evolved to be at the forefront of food formulation and development. Food Texture Design and Optimization presents the latest insights in food texture derived from advances in formulation science as well as sensory and instrumental measurement. This unique volume provides practical insights for professionals who are starting in the field as well as experts looking to enhance their knowledge or expand into new areas. The first part of this book presents case studies on formulating products in a broad variety of application segments, such as cheese, ice-cream, baked goods, gluten-free products, low-fat/non-fat dairy products and more. Challenges related to maintaining texture while optimizing nutritional content, cost, flavor and other attributes of the food product are investigated. The book also highlights the importance of texture design and optimization in several types of food products and demonstrates how experts have applied this knowledge in the industry. Part two provides an overview of the latest advances in tools and techniques for food texture design and optimization, focusing on the use of instrumental techniques, the application of sensory techniques, and the use of marketing and consumer insight tools in the design and optimization of food products. The ability to use advanced characterization techniques in this field is critical for both new and established practitioners in tackling the problems they face. Food Texture Design and Optimization serves as an important reference for technical practitioners on how to adopt advanced techniques in food texture research. This information is invaluable in reviewing establish the state of the art in this field and providing a minimum recommended standard for food formulators.

Handbook of Muscle Foods Analysis

Author: Leo M.L. Nollet

Publisher: CRC Press

Published: 2008-11-10

Total Pages: 990

ISBN-13: 142004530X

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In today's nutrition-conscious society, there is a growing awareness among meat scientists and consumers about the importance of the essential amino acids, vitamins, and minerals found in muscle foods. Handbook of Muscle Foods Analysis provides a comprehensive overview and description of the analytical techniques and application methodologies for t