Feature Extraction And Image Processing

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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 : 50,7 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

Feature Extraction and Image Processing

Mark Nixon
Feature Extraction and Image Processing Book PDF

Author : Mark Nixon
Publisher : Elsevier
Page : 364 pages
File Size : 48,5 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

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 : 55,9 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.

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 : 47,7 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.

Content-Based Image Classification

Rik Das
Content Based Image Classification Book PDF

Author : Rik Das
Publisher : CRC Press
Page : 197 pages
File Size : 47,8 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/

Handbook of Image Processing and Computer Vision

Arcangelo Distante,Cosimo Distante
Handbook of Image Processing and Computer Vision Book PDF

Author : Arcangelo Distante,Cosimo Distante
Publisher : Springer Nature
Page : 507 pages
File Size : 44,8 Mb
Release : 2020-05-28
Category : Computers
ISBN : 9783030381486

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Handbook of Image Processing and Computer Vision by Arcangelo Distante,Cosimo Distante Pdf

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.

Feature Extraction and Image Processing for Computer Vision

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

Author : Mark Nixon,Alberto Aguado
Publisher : Academic Press
Page : 650 pages
File Size : 48,8 Mb
Release : 2019-11-17
Category : Computers
ISBN : 9780128149775

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

Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. 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 link between theory and exemplar code of the algorithms." Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation. The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour) Good balance between providing a mathematical background and practical implementation Detailed and explanatory of algorithms in MATLAB and Python

Robotic Vision

Peter Corke
Robotic Vision Book PDF

Author : Peter Corke
Publisher : Springer Nature
Page : 412 pages
File Size : 40,5 Mb
Release : 2021-10-15
Category : Technology & Engineering
ISBN : 9783030791759

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Robotic Vision by Peter Corke Pdf

This textbook offers a tutorial introduction to robotics and Computer Vision which is light and easy to absorb. The practice of robotic vision involves the application of computational algorithms to data. Over the fairly recent history of the fields of robotics and computer vision a very large body of algorithms has been developed. However this body of knowledge is something of a barrier for anybody entering the field, or even looking to see if they want to enter the field — What is the right algorithm for a particular problem?, and importantly: How can I try it out without spending days coding and debugging it from the original research papers? The author has maintained two open-source MATLAB Toolboxes for more than 10 years: one for robotics and one for vision. The key strength of the Toolboxes provide a set of tools that allow the user to work with real problems, not trivial examples. For the student the book makes the algorithms accessible, the Toolbox code can be read to gain understanding, and the examples illustrate how it can be used —instant gratification in just a couple of lines of MATLAB code. The code can also be the starting point for new work, for researchers or students, by writing programs based on Toolbox functions, or modifying the Toolbox code itself. The purpose of this book is to expand on the tutorial material provided with the toolboxes, add many more examples, and to weave this into a narrative that covers robotics and computer vision separately and together. The author shows how complex problems can be decomposed and solved using just a few simple lines of code, and hopefully to inspire up and coming researchers. The topics covered are guided by the real problems observed over many years as a practitioner of both robotics and computer vision. It is written in a light but informative style, it is easy to read and absorb, and includes a lot of Matlab examples and figures. The book is a real walk through the fundamentals light and color, camera modelling, image processing, feature extraction and multi-view geometry, and bring it all together in a visual servo system. “An authoritative book, reaching across fields, thoughtfully conceived and brilliantly accomplished Oussama Khatib, Stanford

Biomedical Image Processing

Thomas Martin Deserno
Biomedical Image Processing Book PDF

Author : Thomas Martin Deserno
Publisher : Springer Science & Business Media
Page : 617 pages
File Size : 43,8 Mb
Release : 2011-03-01
Category : Science
ISBN : 9783642158162

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Biomedical Image Processing by Thomas Martin Deserno Pdf

In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics.

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 : 43,9 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.

Data Analytics in Bioinformatics

Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang
Data Analytics in Bioinformatics Book PDF

Author : Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang
Publisher : John Wiley & Sons
Page : 433 pages
File Size : 44,9 Mb
Release : 2021-01-20
Category : Computers
ISBN : 9781119785606

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Data Analytics in Bioinformatics by Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang Pdf

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Knowledge Acquisition: Approaches, Algorithms and Applications

Debbie Richards
Knowledge Acquisition Approaches Algorithms and Applications Book PDF

Author : Debbie Richards
Publisher : Springer Science & Business Media
Page : 252 pages
File Size : 41,8 Mb
Release : 2009-05-25
Category : Computers
ISBN : 9783642017148

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Knowledge Acquisition: Approaches, Algorithms and Applications by Debbie Richards Pdf

This book constitutes the thoroughly refereed post-workshop proceedings of the 2008 Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, held in Hanoi, Vietnam, in December 2008 as part of 10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008. The 20 revised papers presented were carefully reviewed and selected from 57 submissions and went through two rounds of reviewing and improvement. The papers are organized in topical sections on machine learning and data mining, incremental knowledge acquisition, web-based techniques and applications, as well as domain specific knowledge acquisition methods and applications.

Image Processing and Pattern Recognition

Frank Y. Shih
Image Processing and Pattern Recognition Book PDF

Author : Frank Y. Shih
Publisher : John Wiley & Sons
Page : 564 pages
File Size : 53,6 Mb
Release : 2010-05-03
Category : Technology & Engineering
ISBN : 9780470404614

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Image Processing and Pattern Recognition by Frank Y. Shih Pdf

A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.

Digital Image Processing and Analysis

Scott E Umbaugh
Digital Image Processing and Analysis Book PDF

Author : Scott E Umbaugh
Publisher : CRC Press
Page : 980 pages
File Size : 44,5 Mb
Release : 2010-11-19
Category : Computers
ISBN : 9781439802069

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Digital Image Processing and Analysis by Scott E Umbaugh Pdf

Whether for computer evaluation of otherworldly terrain or the latest high definition 3D blockbuster, digital image processing involves the acquisition, analysis, and processing of visual information by computer and requires a unique skill set that has yet to be defined a single text. Until now. Taking an applications-oriented, engineering approach

Supervised and Unsupervised Pattern Recognition

Evangelia Miche Tzanakou
Supervised and Unsupervised Pattern Recognition Book PDF

Author : Evangelia Miche Tzanakou
Publisher : CRC Press
Page : 441 pages
File Size : 48,7 Mb
Release : 2017-12-19
Category : Technology & Engineering
ISBN : 9781351835558

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Supervised and Unsupervised Pattern Recognition by Evangelia Miche Tzanakou Pdf

There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images. This substantial collection of recent research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy neural networks and their applications to handwritten character recognition and recognition of normal and abnormal visual evoked potentials. The third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional NN architecture simulating brain functions. The final section discusses general applications and simulations, such as the establishment of a brain-computer link, speaker identification, and face recognition. In the quickly changing field of computational intelligence, every discovery is significant. Supervised and Unsupervised Pattern Recognition gives you access to many notable findings in one convenient volume.