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The author presents a vision model that uses color information to interpret the effects of shading and highlights on a scene. Transcending more traditional approaches, this method may lead to more reliable and useful techniques for image understanding.
An introduction to color in three-dimensional image processing and the emerging area of multi-spectral image processing The importance of color information in digital image processing is greater than ever. However, the transition from scalar to vector-valued image functions has not yet been generally covered in most textbooks. Now, Digital Color Image Processing fills this pressing need with a detailed introduction to this important topic. In four comprehensive sections, this book covers: The fundamentals and requirements for color image processing from a vector-valued viewpoint Techniques for preprocessing color images Three-dimensional scene analysis using color information, as well as the emerging area of multi-spectral imaging Applications of color image processing, presented via the examination of two case studies In addition to introducing readers to important new technologies in the field, Digital Color Image Processing also contains novel topics such as: techniques for improving three-dimensional reconstruction, three-dimensional computer vision, and emerging areas of safety and security applications in luggage inspection and video surveillance of high-security facilities. Complete with full-color illustrations and two applications chapters, Digital Color Image Processing is the only book that covers the breadth of the subject under one convenient cover. It is written at a level that is accessible for first- and second-year graduate students in electrical and computer engineering and computer science courses, and that is also appropriate for researchers who wish to extend their knowledge in the area of color image processing.
This collective work identifies the latest developments in the field of the automatic processing and analysis of digital color images. For researchers and students, it represents a critical state of the art on the scientific issues raised by the various steps constituting the chain of color image processing. It covers a wide range of topics related to computational color imaging, including color filtering and segmentation, color texture characterization, color invariant for object recognition, color and motion analysis, as well as color image and video indexing and retrieval. Contents 1. Color Representation and Processing in Polar Color Spaces, Jesús Angulo, Sébastien Lefèvre and Olivier Lezoray. 2. Adaptive Median Color Filtering, Frédérique Robert-Inacio and Eric Dinet. 3. Anisotropic Diffusion PDEs for Regularization of Multichannel Images: Formalisms and Applications, David Tschumperlé. 4. Linear Prediction in Spaces with Separate Achromatic and Chromatic Information,Olivier Alata, Imtnan Qazi, Jean-Christophe Burie and Christine Fernandez-Maloigne. 5. Region Segmentation, Alain Clément, Laurent Busin, Olivier Lezoray and Ludovic Macaire. 6. Color Texture Attributes, Nicolas Vandenbroucke, Olivier Alata, Christèle Lecomte, Alice Porebski and Imtnan Qazi. 7. Photometric Color Invariants for Object Recognition, Damien Muselet. 8. Color Key Point Detectors and Local Color Descriptors, Damien Muselet and Xiaohu Song. 9. Motion Estimation in Color Image Sequences, Bertrand Augereau and Jenny Benois-Pineau.
Color Image Processing: Methods and Applications embraces two decades of extraordinary growth in the technologies and applications for color image processing. The book offers comprehensive coverage of state-of-the-art systems, processing techniques, and emerging applications of digital color imaging. To elucidate the significant progress in specialized areas, the editors invited renowned authorities to address specific research challenges and recent trends in their area of expertise. The book begins by focusing on color fundamentals, including color management, gamut mapping, and color constancy. The remaining chapters detail the latest techniques and approaches to contemporary and traditional color image processing and analysis for a broad spectrum of sophisticated applications, including: Vector and semantic processing Secure imaging Object recognition and feature detection Facial and retinal image analysis Digital camera image processing Spectral and superresolution imaging Image and video colorization Virtual restoration of artwork Video shot segmentation and surveillance Color Image Processing: Methods and Applications is a versatile resource that can be used as a graduate textbook or as stand-alone reference for the design and the implementation of various image and video processing tasks for cutting-edge applications. This book is part of the Digital Imaging and Computer Vision series.
"The main theme of the 1988 workshop, the 18th in this DARPA sponsored series of meetings on Image Understanding and Computer Vision, is to cover new vision techniques in prototype vision systems for manufacturing, navigation, cartography, and photointerpretation." P. v.
This book constitutes the refereed proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2001, held in Sophia Antipolis, France in September 2001. The 42 revised full papers presented were carefully reviewed and selected from 70 submissions. The book offers topical sections on probabilistic models and estimation; image modeling and synthesis; clustering, grouping, and segmentation; optimization and graphs; and shapes, curves, surfaces, and templates.
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.
1. The present state and the future of colour image processing; 2. Colour vison; 2.1 What is colous?; 2.2 The visual pathway; 2.3 Light absorption and trichromacy; 2.4 Colour appearance and opponet processes; 2.5 Other phenomena; 2.6 The uses of colour; 3. Colour science; 3.1 Introduction; 3.2 The CIE system; 3.3 Colour measurement instruments; 3.4 Uniform colour spaces and colour difference formulas; 3.5 Colour appearance modelling; 4. Colour spaces; 4.1 Basic RGB colour space; 4.2 XYZ colour spae; 4.3 Television colour spaces; 4.4 Opponent colour space; 4.5 Ohta I1I2I3 colour space; 4.6 IHS and related percentual colour spaces; 4.7 Perceptually unifor colour spaces; 4.8 Munsell colour system; 4.9 Kodak Photo YCC colour space; 4.10 Summary of colour space properties. 5. Colour video systems and signals; 5.1 Video communication; 5.2 Colour reproduction; 5.3 Encoded-colour systems; 6. Image sources; 6.1 Overview of sources for image processing; 6.2 Cameras; 7. Practical system considerations; 7.1 Image acquisition technique; 7.2 Image storage; 7.3 Colorimetric calibration of acquisition hardware; 8. Noise removal and contrast enhancement; 8.1 Noise removal; 8.2 Contrast enhancement; 9. Segmentation and edge detection; 9.1 Pixel-based segmentation; 9.2 Region-based segmentation; 9.3 Edge detection and boundary tracking; 9.4 Segmentation adn edge detection quality metrics; 10 Vector filtering; 10.1 the vector median filter; 10.2 Vector direcitonal filters; 10.3 Adaptive vector processing filters; 10.4 Application to colour images; 11. Morphological operations; 11.1 Mathematical morphology; Colour morphology; 11.3 Multiscale image analysis; 11.4 Image enhancement; 12. Frequenci domain methods; 12.1 Review of the 2D discrete Fourier transform; 12.2 Complex chromaticity; 12.3 The quaternion Fourier transform; 12.4 Disicussion; 13. Compression; 13.1 Image and video compression; 13.2 Component-wise still image compression; 13.3 Exploitation of mutual colour component dependencies; 13.4 Colour video comression; 14. Colour management for the textile industry; 14.1 Overviwe of colour flow in the textile industry; 14.2 Colour management systems; 14.3 CRT characterization; 14.4 WYSIWYG colour management; 14.5 Colour notation; 14.6 Colour quality control; 14.7 The colour talk system; 15. Colour management for the graphic arts; 15.1 Overview of the graphic arts environment; 15.2 Colour management systems overview; 15.3 Characterization and calibration of system components; 15.4 Gamut mapping; 15.5 Current colour management systems; 16 Medical imaging case study; 16.1 Wound metrics: the background and motiviation; 16.2 Principle of structured ligh; 16.3 Implementatin of the status of healing; 16.4 Assessment of the status of healing; 16.5 Automatic segmentation of the wound; 16.6 Visualization and storage of data; 17. Industrial colour inspection case studies; 17.1 Inspection of printed card; 17.2 Inspection of fast-moving beverage cans; References; Index.
This volume in the Springer Lecture Notes in Computer Science (LNCS) series contains 98 papers presented at the S+SSPR 2008 workshops. S+SSPR 2008 was the sixth time that the SPR and SSPR workshops organized by Technical Committees, TC1 and TC2, of the International Association for Pattern Rec- nition (IAPR) wereheld as joint workshops. S+SSPR 2008was held in Orlando, Florida, the family entertainment capital of the world, on the beautiful campus of the University of Central Florida, one of the up and coming metropolitan universities in the USA. S+SSPR 2008 was held during December 4–6, 2008 only a few days before the 19th International Conference on Pattern Recog- tion(ICPR2008),whichwasheldin Tampa,onlytwo hoursawayfromOrlando, thus giving the opportunity of both conferences to attendees to enjoy the many attractions o?ered by two neighboring cities in the state of Florida. SPR 2008 and SSPR 2008 received a total of 175 paper submissions from many di?erent countries around the world, thus giving the workshop an int- national clout, as was the case for past workshops. This volume contains 98 accepted papers: 56 for oral presentations and 42 for poster presentations. In addition to parallel oral sessions for SPR and SSPR, there was also one joint oral session with papers of interest to both the SPR and SSPR communities. A recent trend that has emerged in the pattern recognition and machine lea- ing research communities is the study of graph-based methods that integrate statistical andstructural approaches.