Symbolic Projection For Image Information Retrieval And Spatial Reasoning
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Symbolic Projection for Image Information Retrieval and Spatial Reasoning
Information systems with an abundance of graphics data are growing rapidly due to advances in data storage technology, the development of multimedia communications across networks, and the fact that parallel computers are leading to faster image processing systems. This book addresses image information retrieval and spatial reasoning using an approach called Symbolic Projection, which supports descriptions of the image content on the basis of the spatial relationships between the pictorial objects. Image information systems have a wide variety of applications, including information retrieval on the World Wide Web, medical pictorial archiving, computer-aided design, robotics, and geographical information systems, and this book is comprehensively illustrated with examples from these areas. Symbolic Projection now forms the basis of an enormous number and range of information retrieval algorithms, and also supports query-by-picture and qualitative spatial reasoning. Both authors are international experts in the field, and the book will serve as an excellent source for those working in multimedia systems and image information systems who wish to find out more about this exciting area. - An all-inclusive source to the field--all you need to know - S-K. Chang is the leading authority in this field, which he pioneered - Includes a wide variety of applications, including information retrieval on the World Wide Web, computer-aided design, and geographical information systems
Image Description and Retrieval
Author: Enrico Vicario
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
With the recent advances in multimedia technology, on-line libraries of digital images are assuming an ever increasing relevance within a wide range of information systems. Effective access to such archives requires on external textual keywords that conventional searching techniques based are complemented by content-based queries addressing appearing visual features of searched data. Central to this retrieval approach is the creation of models, which permit to abstract images into some space of features and support indexing and comparison of visual contents. Depending on the specific characteris tics of the images at hand, such models can rely on different facets of the informative contents of visual data: color and texture distribution, shape of appearing objects, spatial arrangement. This book introduces and exemplifies objectives and research themes in image modeling and retrieval. In the introductory chapter, the problem of image modeling and retrieval is motivated and discussed, and major entry-pointers to the literature are provided. Afterwards, different model ing approaches are addressed in six chapters contributed by major research groups in the field: modeling based on object shape is addressed in chapter 2 by F. Korn, N. Sidiropoulos, C. Faloutsos, E. Siegel, and Z. Protopapas, and in chapter 3 by R. Mehrotra and J. E. Gary; modeling based on color and texture distribution is addressed in chapter 4 by G. D. Finlayson, S. S. Chat terjee, and B. V. Funt, and in chapter 5 by I. Gagliardi, A.
Image: E-learning, Understanding, Information Retrieval, Medical - Proceedings Of The First International Workshop
This volume emphasizes the primary role played by images in computer science. In the last two decades images have replaced written texts; the enormous possibilities of the image language have overcome written language in an ever-more-restricted ambit.An image is better than one thousand words; so it was straightforward to apply visual language in the field of computer science. Nowadays everything that appears on a computer screen is an image, regardless of whether it is a word or a picture. Is it possible to realize an e-learning program without working in terms of images? The answer is undoubtedly no, even if several problems arise in this context: the qualitative and quantitative content of the image we need to use for a specific task; the psychological effect on the user, including the level of attention and the correct perception of the image significance. Most of these problems form the basis of image-understanding techniques.Widespread use of images requires organization of the information in the databank or database, whose dimensions are sometimes so wide as to be too complex to manage; therefore information retrieval techniques arise from this need. The new instruments used in image and/or remote diagnosis, image transmission, the respect of the law in force and the ever-more-relevant image storage capacity required for this task imply the use of techniques of visual language and information retrieval.The proceedings have been selected for coverage in:• Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings)• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)