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Top image-processing books mentioned on stackoverflow.com

Purely Functional Data Structures

Chris Okasaki

This book describes data structures and data structure design techniques for functional languages.

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Learning OpenCV

Gary Bradski, Adrian Kaehler

Describes the features and functions of OpenCV along with information on how to build applications using computer vision.

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Programming WCF Services

Juval Lowy

Provides information on developing service-oriented applications for Windows.

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Computer Graphics

James D. Foley

A guide to the concepts and applications of computer graphics covers such topics as interaction techniques, dialogue design, and user interface software.

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Digital Image Processing

Rafael C. Gonzalez, Richard Eugene Woods

A comprehensive digital image processing book that reflects new trends in this field such as document image compression and data compression standards. The book includes a complete rewrite of image data compression, a new chapter on image analysis, and a new section on image morphology.

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Pattern Recognition and Machine Learning

Christopher M. Bishop

The field of pattern recognition has undergone substantial development over the years. This book reflects these developments while providing a grounding in the basic concepts of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as well as researchers and practitioners.

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Multiple View Geometry in Computer Vision

Richard Hartley, Andrew Zisserman

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

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Compressed Image File Formats

John Miano

Since not all graphic formats are of equal complexity, author John Miano does not simply choose a number of file formats and devote a chapter to each one. Instead, he offers additional coverage for the more complex image file formats like PNG (a new standard) and JPEG, while providing all information necessary to use the simpler file formats. While including the well-documented BMP, XBM, and GIF formats for completeness, along with some of their less-covered features, this book gives the most space to the more intricate PNG and JPEG, from basic concepts to creating and reading actual files. Among its highlights, this book covers: -- JPEG Huffman coding, including decoding sequential mode JPEG images and creating sequential JPEG files-- Optimizing the DCT-- Portable Network Graphics format (PNG), including decompressing PNG image data and creating PNG files-- Windows BMP, XBM, and GIF

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Pattern classification

Richard O. Duda, Peter E. Hart, David G. Stork

This edition has been completely revised, enlarged and formatted in two colour. It is a systematic account of the major topics in pattern recognition, based on the fundamental principles. It includes extensive examples, exercises and a solutions manual.

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OpenGL Programming Guide

Dave Shreiner

OpenGL is a powerful software interface used to produce high-quality, computer-generated images and interactive applications using 2D and 3D objects, bitmaps, and color images. The OpenGL ® Programming Guide, Seventh Edition , provides definitive and comprehensive information on OpenGL and the OpenGL Utility Library. The previous edition covered OpenGL through Version 2.1. This seventh edition of the best-selling “red book” describes the latest features of OpenGL Versions 3.0 and 3.1. You will find clear explanations of OpenGL functionality and many basic computer graphics techniques, such as building and rendering 3D models; interactively viewing objects from different perspective points; and using shading, lighting, and texturing effects for greater realism. In addition, this book provides in-depth coverage of advanced techniques, including texture mapping, antialiasing, fog and atmospheric effects, NURBS, image processing, and more. The text also explores other key topics such as enhancing performance, OpenGL extensions, and cross-platform techniques. This seventh edition has been updated to include the newest features of OpenGL Versions 3.0 and 3.1, including Using framebuffer objects for off-screen rendering and texture updates Examples of the various new buffer object types, including uniform-buffer objects, transform feedback buffers, and vertex array objects Using texture arrays to increase performance when using numerous textures Efficient rendering using primitive restart and conditional rendering Discussion of OpenGL's deprecation mechanism and how to verify your programs for future versions of OpenGL This edition continues the discussion of the OpenGL Shading Language (GLSL) and explains the mechanics of using this language to create complex graphics effects and boost the computational power of OpenGL. The OpenGL Technical Library provides tutorial and reference books for OpenGL. The Library enables programmers to gain a practical understanding of OpenGL and shows them how to unlock its full potential. Originally developed by SGI, the Library continues to evolve under the auspices of the Khronos OpenGL ARB Working Group, an industry consortium responsible for guiding the evolution of OpenGL and related technologies.

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The Visual Display of Quantitative Information

Edward R. Tufte

Graphical practice. Theory of data graphics.

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Geometric Tools for Computer Graphics

Philip J. Schneider, David H. Eberly

A collection of proven solutions to fundamental problems, including building primitives, distance calculation, approximation, containment, decomposition, intersection determination, separation, and more. This work covers problems relevant for both 2D and 3D graphics programming.

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Inner Loops

Rick Booth

With practical advice and a broad sampling of important algorithms, Inner Loops shows how to design programs that extend the edge of the envelope of PC performance. It provides a thorough review of 32-bit code optimization for the 486, Pentium and Pentium Pro, as well as design tips for writing fast 32-bit software.

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Computer Vision

David Forsyth, Jean Ponce

The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

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Computational Geometry in C

Joseph O'Rourke

This is the newly revised and expanded edition of the popular introduction to the design and implementation of geometry algorithms arising in areas such as computer graphics, robotics, and engineering design. The second edition contains material on several new topics, such as randomized algorithms for polygon triangulation, planar point location, 3D convex hull construction, intersection algorithms for ray-segment and ray-triangle, and point-in-polyhedron. A new "Sources" chapter points to supplemental literature for readers needing more information on any topic. A novel aspect is the inclusion of working C code for many of the algorithms, with discussion of practical implementation issues. The self-contained treatment presumes only an elementary knowledge of mathematics, but reaches topics on the frontier of current research, making it a useful reference for practitioners at all levels. The code in this new edition is significantly improved from the first edition, and four new routines are included. Java versions for this new edition are also available. All code is accessible from the book's Web site (http://cs.smith.edu/~orourke/) or by anonymous ftp.

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Computational Geometry

Mark de Berg, Otfried Cheong, Marc van Kreveld, Mark Overmars

This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.

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Character Recognition Systems

Mohamed Cheriet, Nawwaf Kharma, Cheng-Lin Liu, Ching Suen

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Image Processing and Analysis

Tony F. Chan, Jianhong (Jackie) Shen

This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.

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Programming with the Kinect for Windows Software Development Kit

David Catuhe

Create rich experiences for users of Windows 7 and Windows 8 Developer Preview with this pragmatic guide to the Kinect for Windows Software Development Kit (SDK). The author, a developer evangelist for Microsoft, walks you through Kinect sensor technology and the SDK--providing hands-on insights for how to add gesture and posture recognition to your apps. If you're skilled in C# and Windows Presentation Foundation, you'll learn how to integrate Kinect in your applications and begin writing Uis and controls that can handle Kinect interaction. This book introduces the Kinect for Windows Software Development Kit to developers looking to enrich applications they build for Windows 7 and later with human motion tracking Teaches developers with core C# and WPF skills how to program gesture and posture recognition in Kinect Describes how to integrate 3D representation on top of a real scene Provides expert insights and code samples to get you up and running

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Semiology of Graphics

Jacques Bertin, William J. Berg

Originally published in French in 1967, "Semiology of Graphics" holds a significant place in the theory of information design. It presents a close study of graphic techniques including shape, orientation, color, texture, volume, and size in an array of more than 1,000 maps and diagrams.

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Digital Image Processing

Rafael C. Gonzalez, Richard Eugene Woods

For courses in Image Processing and Computer Vision. Completely self-contained and heavily illustrated this introduction to basic concepts and methodologies for digital image processing is written at a level that truly is suitable for seniors and first-year graduate students in almost any technical discipline. The leading textbook in its field for more than twenty years, it continues its cutting-edge focus on contemporary developments in all mainstream areas of image processing e.g., image fundamentals, image enhancement in the spatial and frequency domains, restoration, color image processing, wavelets, image compression, morphology, segmentation, image description, and the fundamentals of object recognition. It focuses on material that is fundamental and has a broad scope of application.

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Digital Image Processing

Wilhelm Burger, Mark J. Burge

Written as an introduction for undergraduate students, this textbook covers the most important methods in digital image processing. Formal and mathematical aspects are discussed at a fundamental level and various practical examples and exercises supplement the text. The book uses the image processing environment ImageJ, freely distributed by the National Institute of Health. A comprehensive website supports the book, and contains full source code for all examples in the book, a question and answer forum, slides for instructors, etc. Digital Image Processing in Java is the definitive textbook for computer science students studying image processing and digital processing.

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The Image Processing Handbook, Fourth Edition

John C. Russ

This essential resource covers binary image processing, color images, depth resolution, image interpretation problems, thresholding multiband images, among many other areas of image analysis and processing.

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Digital image warping

George Wolberg

This best-selling, original text focuses on image reconstruction, real-time texture mapping, separable algorithms, two-pass transforms, mesh warping, and special effects. The text, containing all original material, begins with the history of the field and continues with a review of common terminology, mathematical preliminaries, and digital image acquisition. Later chapters discuss equations for spatial information, interpolation kernels, filtering problems, and fast-warping techniques based on scanline algorithms.

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Pro Android Augmented Reality

Raghav Sood

Augmented reality (AR) offers a live direct or indirect view of a physical, real-world environment, where the elements and surroundings are augmented by computer-generated sensory input such as graphics and GPS data. It makes a game more real. Your social media app puts you where want to be or go. Pro Android Augmented Reality walks you through the foundations of building an augmented reality application. From using various software and Android hardware sensors, such as an accelerometer or a magnetometer (compass), you'll learn the building blocks of augmented reality for both marker- and location-based apps. Case studies are included in this one-of-a-kind book, which pairs nicely with other Android development books. After reading Pro Android Augmented Reality, you'll be able to build augmented reality rich media apps or integrate all the best augmented reality into your favorite Android smartphone and/or tablet. What you’ll learn How to use most Android cameras How to find the user's location with GPS data How to detect movement and orientation of the device How to program against the accelerometer and compass How to use the AndAR library in marker recognition How to create an artificial horizon for your app How to integrate the Google Maps API into AR apps How to build enterprise augmented reality apps using the case studies in this book Who this book is for This book is for Android developers familiar with Android programming, but new to the camera, accelerometer, magnetometer and building augmented reality applications in general. Table of Contents Applications of Augmented Reality Basics of Augmented Reality on the Android Platform Adding Overlays Artificial Horizons Other Features of Augmented Reality A Simple App Using AR A More Complex Project Using More AR Features A Project Using All AR Features An AR Game

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Pattern Recognition and Neural Networks

Brian D. Ripley

Ripley brings together two crucial ideas in pattern recognition: statistical methods and machine learning via neural networks. He brings unifying principles to the fore, and reviews the state of the subject. Ripley also includes many examples to illustrate real problems in pattern recognition and how to overcome them.

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Data mining

Ian H. Witten, Eibe Frank

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Digital Image Processing Using MATLAB

Rafael C. Gonzalez, Richard Eugene Woods, Steven L. Eddins

Solutions to problems in the field of digital image processing generally require extensive experimental work involving software simulation and testing with large sets of sample images. Although algorithm development typically is based on theoretical underpinnings, the actual implementation of these algorithms almost always requires parameter estimation and, frequently, algorithm revision and comparison of candidate solutions. Thus, selection of a flexible, comprehensive, and well-documented software development environment is a key factor that has important implications in the cost, development time, and portability of image processing solutions. In spite of its importance, surprisingly little has been written on this aspect of the field in the form of textbook material dealing with both theoretical principles and software implementation of digital image processing concepts. This book was written for just this purpose. Its main objective is to provide a foundation for implementing image processing algorithms using modern software tools. A complementary objective was to prepare a book that is self-contained and easily readable by individuals with a basic background in digital image processing, mathematical analysis, and computer programming, all at a level typical of that found in a junior/senior curriculum in a technical discipline. Rudimentary knowledge of MATLAB also is desirable. To achieve these objectives, we felt that two key ingredients were needed. The first was to select image processing material that is representative of material covered in a formal course of instruction in this field. The second was to select software tools that are well supported and documented, and which have a wide range of applications in the "real" world. To meet the first objective, most of the theoretical concepts in the following chapters were selected fromDigital Image Processingby Gonzalez and Woods, which has been the choice introductory textbook used by educators all over the world for over two decades. The software tools selected are from the MATLAB Image Processing Toolbox (IPT), which similarly occupies a position of eminence in both education and industrial applications. A basic strategy followed in the preparation of the book was to provide a seamless integration of well-established theoretical concepts and their implementation using state-of-the-art software tools. The book is organized along the same lines asDigital Image Processing.In this way, the reader has easy access to a more detailed treatment of all the image processing concepts discussed here, as well as an up-to-date set of references for further reading. Following this approach made it possible to present theoretical material in a succinct manner and thus we were able to maintain a focus on the software implementation aspects of image processing problem solutions. Because it works in the MATLAB computing environment, the Image Processing Toolbox offers some significant advantages, not only f in the breadth of its computational tools, but also because it is supported under most operating systems in use today. A unique feature of this book is its emphasis on showing how to develop new code to enhance existing MATLAB and IPT functionality This is an important feature in an area such as image processing, which, as noted earlier, is characterized by the need for extensive algorithm development and experimental work. After an introduction to the fundamentals of MATLAB functions and programming, the book proceeds to address the mainstream areas of image processing. The major areas covered include intensity transformations, linear and nonlinear spatial filtering, filtering in the frequency domain, image restoration and registration, color image processing, wavelets, image data compression, morphological image processing, image segmentation, region and boundary representation and description, and object recognition. This material is complemented by numerous illustrations of how to solve image processing problems using MATLAB and IPT functions. In cases where a function did not exist, a new function was written and documented as part of the instructional focus of the book. Over 60 new functions are included in the following chapters. These functions increase the scope of IPT by approximately 35 percent and also serve the important purpose of further illustrating how to implement new image processing software solutions. The material is presented in textbook format, not as a software manual. Although the book is self-contained, we have established a companion Web site (see Section 1.5) designed to provide support in a number of areas. For students following a formal course of study or individuals embarked on a program of self study, the site contains tutorials and reviews on background material, as well as projects and image databases, including all images in the book. For instructors, the site contains classroom presentation materials that include PowerPoint slides of all the images and graphics used in the book. Individuals already familiar with image processing and IPT fundamentals will find the site a useful place for up-to-date references, new implementation techniques, and a host of other support material not easily found elsewhere. All purchasers of the book are eligible to download executable files of all the new functions developed in the text. As is true of most writing efforts of this nature, progress continues after work on the manuscript stops. For this reason, we devoted significant effort to the selection of material that we believe is fundamental, and whose value is likely to remain applicable in a rapidly evolving body of knowledge. We trust that readers of the book will benefit from this effort and thus find the material timely and useful in their work.

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Computer Vision

David Forsyth, Jean Ponce

Computer Vision: A Modern Approach, 2e, is appropriate for upper-division undergraduate- and graduate-level courses in computer vision found in departments of Computer Science, Computer Engineering and Electrical Engineering. This textbook provides the most complete treatment of modern computer vision methods by two of the leading authorities in the field. This accessible presentation gives both a general view of the entire computer vision enterprise and also offers sufficient detail for students to be able to build useful applications. Students will learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods

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