Feature Extraction and Image Processing for Computer Vision

Author: Mark Nixon,Alberto Aguado

Publisher: Academic Press

ISBN: 0128149779

Category: Computers

Page: 650

View: 1548

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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
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Computer Vision and Image Processing

Author: Tim Morris

Publisher: Palgrave MacMillan

ISBN: 9780333994511

Category: Computer vision

Page: 300

View: 1720

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Directed at third-year undergraduates and postgraduates, this challenging text offers a complete and up-to-date introduction to computer vision and image processing. Examples in both Java and C++ are used throughout the book making it suitable for a wide range of courses.
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Building Computer Vision Projects with OpenCV 4 and C++

Implement complex computer vision algorithms and explore deep learning and face detection

Author: David Millán Escrivá,Prateek Joshi,Vinícius G. Mendonça,Roy Shilkrot

Publisher: Packt Publishing Ltd

ISBN: 1838641262

Category: Computers

Page: 538

View: 9754

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Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms Key Features Discover best practices for engineering and maintaining OpenCV projects Explore important deep learning tools for image classification Understand basic image matrix formats and filters Book Description OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi What you will learn Stay up-to-date with algorithmic design approaches for complex computer vision tasks Work with OpenCV's most up-to-date API through various projects Understand 3D scene reconstruction and Structure from Motion (SfM) Study camera calibration and overlay augmented reality (AR) using the ArUco module Create CMake scripts to compile your C++ application Explore segmentation and feature extraction techniques Remove backgrounds from static scenes to identify moving objects for surveillance Work with new OpenCV functions to detect and recognize text with Tesseract Who this book is for If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.
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Computer Vision/Computer Graphics Collaboration Techniques

Third International Conference on Computer Vision/Computer Graphics, MIRAGE 2007, Rocquencourt, France, March 28-30, 2007, Proceedings

Author: André Gagalowicz,Wilfried Philips

Publisher: Springer

ISBN: 354071457X

Category: Computers

Page: 620

View: 5517

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This book constitutes the refereed proceedings of the Third International Conference on Computer Vision/Computer Graphics collaboration techniques involving image analysis/synthesis approaches MIRAGE 2007, held in Rocquencourt, France, in March 2007. The 55 revised full cover foundational, methodological, and application issues.
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Pattern Recognition, Machine Intelligence and Biometrics

Author: Patrick S. P. Wang

Publisher: Springer Science & Business Media

ISBN: 3642224075

Category: Computers

Page: 866

View: 8001

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"Pattern Recognition, Machine Intelligence and Biometrics" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland security. In addition, computer modeling and simulations of human behaviors are addressed in this collection of 31 chapters by top-ranked professionals from all over the world in the field of PR/AI/Biometrics. The book is intended for researchers and graduate students in Computer and Information Science, and in Communication and Control Engineering. Dr. Patrick S. P. Wang is a Professor Emeritus at the College of Computer and Information Science, Northeastern University, USA, Zijiang Chair of ECNU, Shanghai, and NSC Visiting Chair Professor of NTUST, Taipei.
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Machine Vision and Advanced Image Processing in Remote Sensing

Proceedings of Concerted Action MAVIRIC (Machine Vision in Remotely Sensed Image Comprehension)

Author: Ioannis Kanellopoulos,Graeme G. Wilkinson,Theo Moons

Publisher: Springer Science & Business Media

ISBN: 3642601057

Category: Science

Page: 335

View: 5461

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Since 1994, the European Commission has undertaken various actions to expand the use of Earth observation (EO) from space in the Union and to stimulate value-added services based on the use of Earth observation satellite data.' By supporting research and technological development activities in this area, DG XII responded to the need to increase the cost-effectiveness of space derived environmental information. At the same time, it has contributed to a better exploitation of this unique technology, which is a key source of data for environmental monitoring from local to global scale. MAVIRIC is part of the investment made in the context of the Environ ment and Climate Programme (1994-1998) to strengthen applied techniques, based on a better understanding of the link between the remote sensing signal and the underlying bio- geo-physical processes. Translation of this scientific know-how into practical algorithms or methods is a priority in order to con vert more quickly, effectively and accurately space signals into geographical information. Now the availability of high spatial resolution satellite data is rapidly evolving and the fusion of data from different sensors including radar sensors is progressing well, the question arises whether existing machine vision approaches could be advantageously used by the remote sensing community. Automatic feature/object extraction from remotely sensed images looks very attractive in terms of processing time, standardisation and implementation of operational processing chains, but it remains highly complex when applied to natural scenes.
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Computer Vision Projects with OpenCV and Python 3

Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow

Author: Matthew Rever

Publisher: Packt Publishing Ltd

ISBN: 1789954908

Category: Computers

Page: 182

View: 9965

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Gain a working knowledge of advanced machine learning and explore Python’s powerful tools for extracting data from images and videos Key Features Implement image classification and object detection using machine learning and deep learning Perform image classification, object detection, image segmentation, and other Computer Vision tasks Crisp content with a practical approach to solving real-world problems in Computer Vision Book Description Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries. What you will learn Install and run major Computer Vision packages within Python Apply powerful support vector machines for simple digit classification Understand deep learning with TensorFlow Build a deep learning classifier for general images Use LSTMs for automated image captioning Read text from real-world images Extract human pose data from images Who this book is for Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.
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Information Systems Design and Intelligent Applications

Proceedings of Third International Conference INDIA 2016

Author: Suresh Chandra Satapathy,Jyotsna Kumar Mandal,Siba K. Udgata,Vikrant Bhateja

Publisher: Springer

ISBN: 8132227573

Category: Computers

Page: 669

View: 9783

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The third international conference on INformation Systems Design and Intelligent Applications (INDIA – 2016) held in Visakhapatnam, India during January 8-9, 2016. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of three different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano-computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not only limited to computer researchers but also include mathematics, chemistry, biology, bio-chemistry, engineering, statistics, and all others in which computer techniques may assist.
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Time-varying image processing and moving object recognition, 2

proceedings of the 3rd international workshop, Florence, Italy, May 29-31, 1989

Author: Vito Cappellini,European Association for Signal Processing

Publisher: North-Holland

ISBN: N.A

Category: Computers

Page: 340

View: 1108

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The new specific area of Time-Varying Image Processing and Moving Object Recognition is attracting increasing interest. This new area is contributing to impressive advances in several fields, such as communications, radar-sonar systems, remote sensing, biomedicine, moving vehicle recognition-tracking, traffic monitoring, automatic inspection and robotics. This volume provides an authoritative and timely review on the latest scientific and technical advances in this area. New digital image processing and recognition methods, implementation techniques and advanced applications are presented. New approaches for solving 3-D problems are described, with particular reference to the recognition and tracking of moving objects. The contributions in this volume, written by internationally renowned experts, will provide both a stimulus for future research in this field as well as useful reference material for many years to come.
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Multiple View Geometry in Computer Vision

Author: Richard Hartley,Andrew Zisserman

Publisher: Cambridge University Press

ISBN: 9780521540513

Category: Computers

Page: 655

View: 9102

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How to reconstruct scenes from images using geometry and algebra, with applications to computer vision.
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