Image Description and Retrieval
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.
1029886178
Image Description and Retrieval
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.
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Image Description and Retrieval

Image Description and Retrieval

Image Description and Retrieval

Image Description and Retrieval

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Overview

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.

Product Details

ISBN-13: 9780306459252
Publisher: Springer-Verlag New York, LLC
Publication date: 09/28/1998
Series: Advances in Computer Vision and Machine
Pages: 194
Product dimensions: 6.30(w) x 9.45(h) x (d)

Table of Contents

1. Image Modeling and Retrieval.- 1.1. Image Archives.- 1.2. The Modal Distance between Images and Text.- 1.3. Reducing Image Complexity through Models.- 1.4. A Three Stage Operation Scheme.- 1.5. Book Contents.- 2. Efficient and Effective Nearest Neighbor Search in a Medical Image Database of Tumor Shapes.- 2.1. Introduction.- 2.2. Survey.- 2.3. Mathematical Morphology.- 2.4. Problem Definition.- 2.5. Proposed Solution.- 2.6. Experiments.- 2.7. Conclusions.- 2.8. Discussion.- Appendices.- 2.A. Proof of Lemma.- 2.B. Proof of Lemma.- 2.C. Proof of Lemma.- 3. Shape-Similarity-Based Retrieval in Image Databases.- 3.1. Introduction.- 3.2. 2-Dimensional Shape Retrieval.- 3.3. 3-Dimensional Shape Retrieval.- 3.4. Conclusions.- 4. Color Angular Indexing and Image Retrieval.- 4.1. Introduction.- 4.2. Background.- 4.3. Distribution Angles.- 4.4. Results.- 4.5. Conclusion.- 5. Indexing Color-Texture Image Patterns.- 5.1. Introduction.- 5.2. Image Indexing Based on Texture and Color.- 5.3. Color Texture Indexing and Retrieval.- 5.4. Evaluation.- 5.5. Conclusions.- 5.6. Acknowledgments.- 6. Iconic Indexing for Visual Databases.- 6.1. Introduction.- 6.2. Background.- 6.3. Generalized Extended Pseudo-Symbolic Pictures.- 6.4. Algorithms for Generating GP-2D and GEP-2D Strings.- 6.5. Maintenance of Lost Absolute Spatial Relationships.- 6.6. The Generalized Combined 2D String Representation.- 6.7. Picture Retrieval by GEP-2D Strings and GC-2D Strings.- 6.8. Discussion and Conclusion.- 6.9. Acknowledgments.- 7. Using Weighted Spatial Relationships in Retrieval by Visual Contents.- 7.1. Introduction.- 7.2. Weighted Walkthroughs.- 7.3. Using Weighted Walkthroughs to Model Spatial Arrangements.- 7.4. Discussion.
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