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Informationen zum Autor THEO GEVERS, PhD, is Professor of Computer Science in the Intelligent Systems Lab at the University of Amsterdam in the Netherlands, and CVC Full Professor at the Computer Vision Center in Barcelona, Spain. ARJAN GIJSENIJ, PhD, was a postdoctoral researcher in the Intelligent Systems Lab at the University of Amsterdam, the Netherlands, while writing this book. JOOST van de WEIJER, PhD, is a Ramon y Cajal Fellow at the Universitat Autònoma de Barcelona, Spain. JAN-MARK GEUSEBROEK, PhD, was assistant professor in the Intelligent Systems Lab at the University of Amsterdam, the Netherlands, while writing this book. Klappentext Comprehensive, up-to-date coverage of computer vision from a color perspective While the field of computer vision drives many of today's digital technologies and communication networks, the topic of color has emerged only recently in most computer vision applications. One of the most extensive works to date on color in computer vision, this book provides a complete set of tools for working with color in the field of image understanding. Based on the authors' intense collaboration for more than a decade and drawing on the latest thinking in the field of computer science, the book integrates topics from color science and computer vision, clearly linking theories, techniques, machine learning, and applications. The fundamental basics, sample applications, and downloadable versions of the software and data sets are also included. Clear, thorough, and practical, Color in Computer Vision explains: Computer vision, including color-driven algorithms and quantitative results of various state-of-the-art methods Color science topics such as color systems, color reflection mechanisms, color invariance, and color constancy Digital image processing, including edge detection, feature extraction, image segmentation, and image transformations Signal processing techniques for the development of both image processing and machine learning Robotics and artificial intelligence, including such topics as supervised learning and classifiers for object and scene categorization Researchers and professionals in computer science, computer vision, color science, electrical engineering, and signal processing will learn how to implement color in computer vision applications and gain insight into future developments in this dynamic and expanding field. Zusammenfassung * Covers the most up-to-date research and latest developments on computer vision * Wide range of topics discussed, including colorimetry, color vision, photometric invariance, all with clear applications to computer vision * FTP site with source code of algorithms, links to data sets from the text . Inhaltsverzeichnis Preface xv 1 Introduction 1 1.1 From Fundamental to Applied 2 1.2 Part I: Color Fundamentals 3 1.3 Part II: Photometric Invariance 3 1.4 Part III: Color Constancy 4 1.5 Part IV: Color Feature Extraction 5 1.6 Part V: Applications 7 1.7 Summary 9 PART I Color Fundamentals 11 2 Color Vision 13 2.1 Introduction 13 2.2 Stages of Color Information Processing 14 2.3 Chromatic Properties of the Visual System 18 2.4 Summary 24 3 Color Image Formation 26 3.1 Lambertian Reflection Model 28 3.2 Dichromatic Reflection Model 29 3.3 Kubelka-Munk Model 32 3.4 The Diagonal Model 34 3.5 Color Spaces 36 3.6 Summary 44 PART II Photometric Invariance 47 4 Pixel-Based Photometric Invariance 49 4.1 Normalized Color Spaces 50 4.2 Opponent Color Spaces 52 4.3 The HSV Color Space 52 4.4 Composed Color Spaces 53 4.5 Noise Stability and Histogram Construction 58 4.6 Application: Color-Based Object Recognition 64 4.7...
