Image Understanding

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Image Understanding Workshop

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Image Understanding

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Foundations Of Image Understanding

Author: Larry S. Davis
Editor: Springer Science & Business Media
ISBN: 1461515297
File Size: 28,52 MB
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Computer systems that analyze images are critical to a wide variety of applications such as visual inspections systems for various manufacturing processes, remote sensing of the environment from space-borne imaging platforms, and automatic diagnosis from X-rays and other medical imaging sources. Professor Azriel Rosenfeld, the founder of the field of digital image analysis, made fundamental contributions to a wide variety of problems in image processing, pattern recognition and computer vision. Professor Rosenfeld's previous students, postdoctoral scientists, and colleagues illustrate in Foundations of Image Understanding how current research has been influenced by his work as the leading researcher in the area of image analysis for over two decades. Each chapter of Foundations of Image Understanding is written by one of the world's leading experts in his area of specialization, examining digital geometry and topology (early research which laid the foundations for many industrial machine vision systems), edge detection and segmentation (fundamental to systems that analyze complex images of our three-dimensional world), multi-resolution and variable resolution representations for images and maps, parallel algorithms and systems for image analysis, and the importance of human psychophysical studies of vision to the design of computer vision systems. Professor Rosenfeld's chapter briefly discusses topics not covered in the contributed chapters, providing a personal, historical perspective on the development of the field of image understanding. Foundations of Image Understanding is an excellent source of basic material for both graduate students entering the field and established researchers who require a compact source for many of the foundational topics in image analysis.

Image Understanding Workshop

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Editor: Morgan Kaufmann
ISBN:
File Size: 77,15 MB
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Image Understanding Workshop

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Editor: Morgan Kaufmann
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File Size: 15,46 MB
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Biomedical Image Understanding

Author: Joo-Hwee Lim
Editor: John Wiley & Sons
ISBN: 1118715152
File Size: 53,53 MB
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With contributions from experts in China, France, Italy, Japan, Singapore, the United Kingdom, and the United States, Biomedical Image Understanding: • Addresses motion tracking and knowledge-based systems, two areas which are not covered extensively elsewhere in a biomedical context • Describes important clinical applications, such as virtual colonoscopy, ocular disease diagnosis, and liver tumor detection • Contains twelve self-contained chapters, each with an introduction to basic concepts, principles, and methods, and a case study or application

Image Understanding 1989

Author: Shimon Ullman
Editor: Intellect Books
ISBN: 9780893915476
File Size: 18,22 MB
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The volumes in this series contain studies in computational vision or image understanding, and explain the computations that underlie the extraction and use of visual information by both biological and artificial systems. Reprints of seminal studies are included along with the original articles.

Multispectral Satellite Image Understanding

Author: Cem Ünsalan
Editor: Springer Science & Business Media
ISBN: 9780857296672
File Size: 21,67 MB
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This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

Image Understanding 1985 86

Author: Whitman Richards
Editor: Intellect Books
ISBN: 9780893913113
File Size: 53,67 MB
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The volumes in this series contain studies in computational vision or image understanding, and explain the computations that underlie the extraction and use of visual information by both biological and artificial systems. Reprints of seminal studies are included along with the original articles.

Image Understanding Using Sparse Representations

Author: Jayaraman J. Thiagarajan
Editor: Morgan & Claypool Publishers
ISBN: 1627053603
File Size: 78,95 MB
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Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blind source separation, super-resolution, and classification. The primary goal of this book is to present the theory and algorithmic considerations in using sparse models for image understanding and computer vision applications. To this end, algorithms for obtaining sparse representations and their performance guarantees are discussed in the initial chapters. Furthermore, approaches for designing overcomplete, data-adapted dictionaries to model natural images are described. The development of theory behind dictionary learning involves exploring its connection to unsupervised clustering and analyzing its generalization characteristics using principles from statistical learning theory. An exciting application area that has benefited extensively from the theory of sparse representations is compressed sensing of image and video data. Theory and algorithms pertinent to measurement design, recovery, and model-based compressed sensing are presented. The paradigm of sparse models, when suitably integrated with powerful machine learning frameworks, can lead to advances in computer vision applications such as object recognition, clustering, segmentation, and activity recognition. Frameworks that enhance the performance of sparse models in such applications by imposing constraints based on the prior discriminatory information and the underlying geometrical structure, and kernelizing the sparse coding and dictionary learning methods are presented. In addition to presenting theoretical fundamentals in sparse learning, this book provides a platform for interested readers to explore the vastly growing application domains of sparse representations.

Image Understanding In Unstructured Environment

Author: Su-shing Chen
Editor: World Scientific
ISBN: 9789971504786
File Size: 72,16 MB
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In the development of autonomous sensory controlled systems, image understanding of sensory data is a difficult but important topic. Due to the unpredictable and uncertain nature of the environment, current image processing and computer vision approaches are not adequate to provide the capabilities needed by the systems. Thus, new approaches are required in the overall system design, including sophisticated reasoning processes, uncertainty management and adaptable architectures. This general issue is addressed by Thomas M Strat and Grahame B Smith. Lashon B Booker discusses the Bayesian approach in plausible reasoning for classification of complex ship images based on incomplete and uncertain evidence. Dynamic scene analysis is treated by Seetharaman Gunasekaran and Tzay Y Young. A spherical perspective approach is introduced to overcome some limitations of the current vision systems by Michael Penna and Su-shing Chen. Finally, Markov image models and their pixel-level approaches are extended to global approaches, through Dempster-Shafer and other techniques, by Mingchuan Zhang and Su-shing Chen.

Proceedings 2005 Symposium On Document Image Understanding Technology

Author: University of Maryland/UMIACS
Editor: UMD
ISBN: 9780977943654
File Size: 38,77 MB
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Proceeding Image Understanding Workshop June 1984

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Body Image

Author: Sarah Grogan
Editor: Psychology Press
ISBN: 0415147859
File Size: 30,89 MB
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Body Image: Understanding Body Dissatisfaction in Men, Women and Children presents a review of what is presently known and the results of some new research on body image. It compares the effects of gender, sexuality, social class, age and ethnicity on satisfaction with the way we look and suggests how these differences arise. Why, for instance, are heterosexual men much happier with their body images than women or gay men? Sarah Grogan discusses the effect of media presentation of the ideal body and other cultural influences. Surprisingly, despite the almost exclusive media preference for very young female bodies, she finds that older women are not less satisfied with their bodies than younger women. Written for readers from a variety of disciplines, this clear and eclectic book will make the ideal text for students from psychology, sociology, gender and media studies.

Image Understanding

Author: Lee S. Baumann
Editor:
ISBN:
File Size: 28,79 MB
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This document contains the technical papers and outlines of semi-annual progress reports presented by the research activities in Image Understanding, sponosred by the Information Processing Techniques Office; Defense Advanced Research Projects Agency. The papers were presented at a workshop conducted on 15-16 September 1982 in Palo Alto, California. (Author).

Image Understanding Workshop

Author: Thomas M. Strat
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File Size: 79,62 MB
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Image Understanding

Author: Lee S. Baumann
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File Size: 16,64 MB
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Medical Image Understanding Technology

Author: Ryszard Tadeusiewicz
Editor: Boom Koninklijke Uitgevers
ISBN: 9783540219859
File Size: 52,67 MB
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A detailed description of a new approach to perceptual analysis and processing of medical images is given. Instead of traditional pattern recognition a new method of image analysis is presented, based on a syntactic description of the shapes selected on the image and graph-grammar parsing algorithms. This method of "Image Understanding" can be found as a model of mans' cognitive image understanding processes. The usefulness for the automatic understanding of the merit of medical images is demonstrated as well as the ability for giving useful diagnostic descriptions of the illnesses. As an application, the production of a content-based, automatically generated index for arranging and for searching medical images in multimedia medical databases is presented.

Image Understanding

Author: Yujin Zhang
Editor: de Gruyter
ISBN: 9783110520347
File Size: 55,85 MB
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This graduate textbook explains image reconstruction technologies based on region-based binocular and trinocular stereo vision, and object, pattern and relation matching. It further discusses principles and applications of multi-sensor fusion and content-based retrieval. Rich in examples and excises, the book concludes image engineering studies for electrical engineering and computer science students.