Texture Feature Extraction Techniques for Image Recognition

Texture Feature Extraction Techniques for Image Recognition PDF Author: Jyotismita Chaki
Publisher: Springer Nature
ISBN: 9811508534
Category : Technology & Engineering
Languages : en
Pages : 109

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Book Description
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.

Texture Feature Extraction Techniques for Image Recognition

Texture Feature Extraction Techniques for Image Recognition PDF Author: Jyotismita Chaki
Publisher: Springer Nature
ISBN: 9811508534
Category : Technology & Engineering
Languages : en
Pages : 109

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Book Description
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

Feature Extraction and Image Processing for Computer Vision PDF Author: Mark Nixon
Publisher: Academic Press
ISBN: 0123978246
Category : Computers
Languages : en
Pages : 629

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Book Description
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

Data Engineering and Intelligent Computing

Data Engineering and Intelligent Computing PDF Author: Suresh Chandra Satapathy
Publisher: Springer
ISBN: 9811032238
Category : Technology & Engineering
Languages : en
Pages : 660

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Book Description
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.

Content-Based Image Classification

Content-Based Image Classification PDF Author: Rik Das
Publisher: CRC Press
ISBN: 1000280470
Category : Computers
Languages : en
Pages : 197

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Book Description
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/

Handbook Of Pattern Recognition And Computer Vision (2nd Edition)

Handbook Of Pattern Recognition And Computer Vision (2nd Edition) PDF Author: Chi Hau Chen
Publisher: World Scientific
ISBN: 9814497649
Category : Computers
Languages : en
Pages : 1045

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Book Description
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.

Feature Extraction and Image Processing

Feature Extraction and Image Processing PDF Author: Mark Nixon
Publisher: Elsevier
ISBN: 0080506259
Category : Computers
Languages : en
Pages : 364

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Book Description
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

Combinatorial Image Analysis

Combinatorial Image Analysis PDF Author: Reinhard Klette
Publisher: Springer Science & Business Media
ISBN: 3540239421
Category : Computers
Languages : en
Pages : 771

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Book Description
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.

Image Color Feature Extraction Techniques

Image Color Feature Extraction Techniques PDF Author: Jyotismita Chaki
Publisher: Springer Nature
ISBN: 9811557616
Category : Technology & Engineering
Languages : en
Pages : 93

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Book Description
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).

Image Processing

Image Processing PDF Author: Yung-Sheng Chen
Publisher: BoD – Books on Demand
ISBN: 9533070269
Category : Computers
Languages : en
Pages : 530

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Book Description
There are six sections in this book. The first section presents basic image processing techniques, such as image acquisition, storage, retrieval, transformation, filtering, and parallel computing. Then, some applications, such as road sign recognition, air quality monitoring, remote sensed image analysis, and diagnosis of industrial parts are considered. Subsequently, the application of image processing for the special eye examination and a newly three-dimensional digital camera are introduced. On the other hand, the section of medical imaging will show the applications of nuclear imaging, ultrasound imaging, and biology. The section of neural fuzzy presents the topics of image recognition, self-learning, image restoration, as well as evolutionary. The final section will show how to implement the hardware design based on the SoC or FPGA to accelerate image processing.

Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing

Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing PDF Author: Kamila, Narendra Kumar
Publisher: IGI Global
ISBN: 1466686553
Category : Computers
Languages : en
Pages : 506

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Book Description
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