Texture Feature Extraction Techniques For Image Recognition

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Texture Feature Extraction Techniques for Image Recognition

Jyotismita Chaki,Nilanjan Dey
Texture Feature Extraction Techniques for Image Recognition Book PDF

Author : Jyotismita Chaki,Nilanjan Dey
Publisher : Springer Nature
Page : 100 pages
File Size : 40,7 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.

Feature Extraction and Image Processing for Computer Vision

Mark Nixon
Feature Extraction and Image Processing for Computer Vision Book PDF

Author : Mark Nixon
Publisher : Academic Press
Page : 629 pages
File Size : 42,5 Mb
Release : 2012-12-18
Category : Computers
ISBN : 9780123978240

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Feature Extraction and Image Processing for Computer Vision by Mark Nixon Pdf

Feature Extraction and Image Processing for Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews Essential reading for engineers and students working in this cutting-edge field Ideal module text and background reference for courses in image processing and computer vision The only currently available text to concentrate on feature extraction with working implementation and worked through derivation

Image Texture Analysis

Chih-Cheng Hung,Enmin Song,Yihua Lan
Image Texture Analysis Book PDF

Author : Chih-Cheng Hung,Enmin Song,Yihua Lan
Publisher : Springer
Page : 264 pages
File Size : 49,5 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.

Image Color Feature Extraction Techniques

Jyotismita Chaki,Nilanjan Dey
Image Color Feature Extraction Techniques Book PDF

Author : Jyotismita Chaki,Nilanjan Dey
Publisher : Springer Nature
Page : 93 pages
File Size : 41,8 Mb
Release : 2020-06-03
Category : Technology & Engineering
ISBN : 9789811557613

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Image Color Feature Extraction Techniques by Jyotismita Chaki,Nilanjan Dey Pdf

This book introduces a range of image color feature extraction techniques. Readers are encouraged to try implementing the techniques discussed here on their own, all of which are presented in a very simple and step-by-step manner. In addition, the book can be used as an introduction to image color feature techniques for those who are new to the research field and software. The techniques are very easy to understand as most of them are described with pictorial examples. Not only the techniques themselves, but also their applications are covered. Accordingly, the book offers a valuable guide to these tools, which are a vital component of content-based image retrieval (CBIR).

Content-Based Image Classification

Rik Das
Content Based Image Classification Book PDF

Author : Rik Das
Publisher : CRC Press
Page : 197 pages
File Size : 42,7 Mb
Release : 2020-12-17
Category : Computers
ISBN : 9781000280470

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Content-Based Image Classification by Rik Das Pdf

Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Image feature extraction with novel handcrafted techniques (traditional feature extraction) Image feature extraction with automated techniques (representation learning with CNNs) Significance of fusion-based approaches in enhancing classification accuracy MATLAB® codes for implementing the techniques Use of the Open Access data mining tool WEKA for multiple tasks The book is intended for budding researchers, technocrats, engineering students, and machine learning/deep learning enthusiasts who are willing to start their computer vision journey with content-based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means for insight generation. Readers will learn coding techniques necessary to propose novel mechanisms and disruptive approaches. The WEKA guide provided is beneficial for those uncomfortable coding for machine learning algorithms. The WEKA tool assists the learner in implementing machine learning algorithms with the click of a button. Thus, this book will be a stepping-stone for your machine learning journey. Please visit the author's website for any further guidance at https://www.rikdas.com/

Feature Extraction and Image Processing

Mark Nixon
Feature Extraction and Image Processing Book PDF

Author : Mark Nixon
Publisher : Elsevier
Page : 364 pages
File Size : 50,7 Mb
Release : 2013-10-22
Category : Computers
ISBN : 9780080506258

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Feature Extraction and Image Processing by Mark Nixon Pdf

Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range of students and professionals. Ideal module text for courses in artificial intelligence, image processing and computer vision Essential reading for engineers and academics working in this cutting-edge field Supported by free software on a companion website

Image Processing

Maria M. P. Petrou,Sei-ichiro Kamata
Image Processing Book PDF

Author : Maria M. P. Petrou,Sei-ichiro Kamata
Publisher : John Wiley & Sons
Page : 816 pages
File Size : 44,7 Mb
Release : 2021-03-22
Category : Technology & Engineering
ISBN : 9781119618553

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Image Processing by Maria M. P. Petrou,Sei-ichiro Kamata Pdf

The classic text that covers practical image processing methods and theory for image texture analysis, updated second edition The revised second edition of Image Processing: Dealing with Textures updates the classic work on texture analysis theory and methods without abandoning the foundational essentials of this landmark work. Like the first, the new edition offers an analysis of texture in digital images that are essential to a diverse range of applications such as: robotics, defense, medicine and the geo-sciences. Designed to easily locate information on specific problems, the text is structured around a series of helpful questions and answers. Updated to include the most recent developments in the field, many chapters have been completely revised including: Fractals and Multifractals, Image Statistics, Texture Repair, Local Phase Features, Dual Tree Complex Wavelet Transform, Ridgelets and Curvelets and Deep Texture Features. The book takes a two-level mathematical approach: light math is covered in the main level of the book, with harder math identified in separate boxes. This important text: Contains an update of the classic advanced text that reviews practical image processing methods and theory for image texture analysis Puts the focus exclusively on an in-depth exploration of texture Contains a companion website with exercises and algorithms Includes examples that are fully worked to enhance the learning experience Written for students and researchers of image processing, the second edition of Image Processing has been revised and updated to incorporate the foundational information on the topic and information on the latest advances.

Handbook Of Texture Analysis

Majid Mirmehdi,Xianghua Xie,Jasjit S Suri
Handbook Of Texture Analysis Book PDF

Author : Majid Mirmehdi,Xianghua Xie,Jasjit S Suri
Publisher : World Scientific
Page : 424 pages
File Size : 40,7 Mb
Release : 2008-10-28
Category : Computers
ISBN : 9781908978929

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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./a

Combinatorial Image Analysis

Reinhard Klette,Jovisa Zunic
Combinatorial Image Analysis Book PDF

Author : Reinhard Klette,Jovisa Zunic
Publisher : Springer Science & Business Media
Page : 771 pages
File Size : 46,6 Mb
Release : 2004-11-22
Category : Computers
ISBN : 9783540239420

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Combinatorial Image Analysis by Reinhard Klette,Jovisa Zunic Pdf

This volume presents the proceedings of the 10th International Workshop on Combinatorial Image Analysis, held December 1–3, 2004, in Auckland, New Zealand. Prior meetings took place in Paris (France, 1991), Ube (Japan, 1992), Washington DC (USA, 1994), Lyon (France, 1995), Hiroshima (Japan, 1997), Madras (India, 1999), Caen (France, 2000), Philadelphia (USA, 2001), and - lermo (Italy, 2003). For this workshop we received 86 submitted papers from 23 countries. Each paper was evaluated by at least two independent referees. We selected 55 papers for the conference. Three invited lectures by Vladimir Kovalevsky (Berlin), Akira Nakamura (Hiroshima), and Maurice Nivat (Paris) completed the program. Conference papers are presented in this volume under the following topical part titles: discrete tomography (3 papers), combinatorics and computational models (6), combinatorial algorithms (6), combinatorial mathematics (4), d- ital topology (7), digital geometry (7), approximation of digital sets by curves and surfaces (5), algebraic approaches (5), fuzzy image analysis (2), image s- mentation (6), and matching and recognition (7). These subjects are dealt with in the context of digital image analysis or computer vision.

A Beginner’s Guide to Image Shape Feature Extraction Techniques

Jyotismita Chaki,Nilanjan Dey
A Beginner s Guide to Image Shape Feature Extraction Techniques Book PDF

Author : Jyotismita Chaki,Nilanjan Dey
Publisher : CRC Press
Page : 147 pages
File Size : 45,6 Mb
Release : 2019-07-25
Category : Computers
ISBN : 9781000034301

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A Beginner’s Guide to Image Shape Feature Extraction Techniques by Jyotismita Chaki,Nilanjan Dey Pdf

This book emphasizes various image shape feature extraction methods which are necessary for image shape recognition and classification. Focussing on a shape feature extraction technique used in content-based image retrieval (CBIR), it explains different applications of image shape features in the field of content-based image retrieval. Showcasing useful applications and illustrating examples in many interdisciplinary fields, the present book is aimed at researchers and graduate students in electrical engineering, data science, computer science, medicine, and machine learning including medical physics and information technology.

Recent Trends in Image Processing and Pattern Recognition

K. C. Santosh,Bharti Gawali
Recent Trends in Image Processing and Pattern Recognition Book PDF

Author : K. C. Santosh,Bharti Gawali
Publisher : Springer Nature
Page : 555 pages
File Size : 43,9 Mb
Release : 2021-02-25
Category : Computers
ISBN : 9789811605079

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Recent Trends in Image Processing and Pattern Recognition by K. C. Santosh,Bharti Gawali Pdf

This two-volume set constitutes the refereed proceedings of the Third International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2020, held in Aurangabad, India, in January 2020. The 78 revised full papers presented were carefully reviewed and selected from 329 submissions. The papers are organized in topical sections in the two volumes. Part I: Computer vision and applications; Data science and machine learning; Document understanding and Recognition. Part II: Healthcare informatics and medical imaging; Image analysis and recognition; Signal processing and pattern recognition; Image and signal processing in Agriculture.

Data Engineering and Intelligent Computing

Suresh Chandra Satapathy,Vikrant Bhateja,K. Srujan Raju,B. Janakiramaiah
Data Engineering and Intelligent Computing Book PDF

Author : Suresh Chandra Satapathy,Vikrant Bhateja,K. Srujan Raju,B. Janakiramaiah
Publisher : Springer
Page : 669 pages
File Size : 47,8 Mb
Release : 2017-05-31
Category : Technology & Engineering
ISBN : 9789811032233

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Data Engineering and Intelligent Computing by Suresh Chandra Satapathy,Vikrant Bhateja,K. Srujan Raju,B. Janakiramaiah Pdf

The book is a compilation of high-quality scientific papers presented at the 3rd International Conference on Computer & Communication Technologies (IC3T 2016). The individual papers address cutting-edge technologies and applications of soft computing, artificial intelligence and communication. In addition, a variety of further topics are discussed, which include data mining, machine intelligence, fuzzy computing, sensor networks, signal and image processing, human-computer interaction, web intelligence, etc. As such, it offers readers a valuable and unique resource.

Texture Analysis in Machine Vision

M K Pietikäinen
Texture Analysis in Machine Vision Book PDF

Author : M K Pietikäinen
Publisher : World Scientific
Page : 280 pages
File Size : 45,9 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

Computer Analysis of Images and Patterns

Wladyslaw Skarbek
Computer Analysis of Images and Patterns Book PDF

Author : Wladyslaw Skarbek
Publisher : Springer
Page : 746 pages
File Size : 48,8 Mb
Release : 2003-06-30
Category : Computers
ISBN : 9783540446927

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Computer Analysis of Images and Patterns by Wladyslaw Skarbek Pdf

Computer analysis of images and patterns is a scienti c eld of longstanding tradition, with roots in the early years of the computer era when electronic brains inspired scientists. Moreover, the design of vision machines is a part of humanity’s dream of the arti cial person. I remember the 2nd CAIP, held in Wismar in 1987. Lectures were read in German, English and Russian, and proceedings were also only partially written in English. The conference took place under a di erent political system and proved that ideas are independent of political walls. A few years later the Berlin Wall collapsed, and Professors Sommer and Klette proposed a new formula for the CAIP: let it be held in Central and Eastern Europe every second year. There was a sense of solidarity with scienti c communities in those countries that found themselves in a state of transition to a new economy. A well-implemented idea resulted in a chain of successful events in Dresden (1991), Budapest (1993), Prague (1995), Kiel (1997), and Ljubljana (1999). This year the conference was welcomed at Warsaw. There are three invited lectures and about 90 contributions written by more than 200 authors from 27 countries. Besides Poland (60 authors), the largest representation comes from France (23), followed by England (16), Czech Republic (11), Spain (10), G- many (9), and Belarus (9). Regrettably, in spite of free registration fees and free accommodation for authors from former Soviet Union countries, we received only one accepted paper from Russia.

Image Feature Detectors and Descriptors

Ali Ismail Awad,Mahmoud Hassaballah
Image Feature Detectors and Descriptors Book PDF

Author : Ali Ismail Awad,Mahmoud Hassaballah
Publisher : Springer
Page : 438 pages
File Size : 46,9 Mb
Release : 2016-02-22
Category : Technology & Engineering
ISBN : 9783319288543

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Image Feature Detectors and Descriptors by Ali Ismail Awad,Mahmoud Hassaballah Pdf

This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition.