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Image Databases: Search and Retrieval of Digital Imagery Edited by Vittorio Castelli, Lawrence D

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Image Databases: Search and Retrieval of Digital Imagery Edited by Vittorio Castelli, Lawrence D Image Databases: Search and Retrieval of Digital Imagery Edited by Vittorio Castelli, Lawrence D. Bergman Copyright 2002 John Wiley & Sons, Inc. ISBNs: 0-471-32116-8 (Hardback); 0-471-22463-4 (Electronic) IMAGE DATABASES IMAGE DATABASES Search and Retrieval of Digital Imagery Edited by Vittorio Castelli Lawrence D. Bergman IBM T.J. Watson Research Center JOHN WILEY & SONS, INC. Designations used by companies to distinguish their products are often claimed as trademarks. In all instances where John Wiley & Sons, Inc., is aware of a claim, the product names appear in initial capital or ALL CAPITAL LETTERS. Readers, however, should contact the appropriate companies for more complete information regarding trademarks and registration. Copyright 2002 by John Wiley & Sons, Inc., New York. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic or mechanical, including uploading, downloading, printing, decompiling, recording or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 605 Third Avenue, New York, NY 10158-0012, (212) 850-6011, fax (212) 850-6008, E-Mail: [email protected]. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold with the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional person should be sought. ISBN 0-471-22463-4 This title is also available in print as ISBN 0-471-32116-8. For more information about Wiley products, visit our web site at www.Wiley.com. To Susan, for her loving support of this work — Vittorio To family and friends, who made this all possible — Larry CONTENTS Contributors xiii Preface xv INTRODUCTION 1 Digital Imagery: Fundamentals 1 Vittorio Castelli and Lawrence D. Bergman 1 1.1 Digital Imagery 1 1.2 Applications of Digital Images 1 1.3 Technological Factors 6 1.4 Indexing Large Collection of Digital Images 8 1.5 Overview of the Book 9 References 10 SELECTED APPLICATION 2 Visible Image Retrieval 11 Carlo Colombo and Alberto Del Bimbo 11 2.1 Introduction 11 2.2 Image Retrieval and Its Applications 12 2.3 Advanced Design Issues 17 2.4 Visible Image Retrieval Examples 22 2.5 Conclusion 31 Acknowledgments 31 References 31 3 Satellite Imagery in Earth Science Applications 35 H.K. Ramapriyan 35 3.1 Introduction 35 3.2 Historical Background and Remote Sensing Missions 36 3.3 Applications of Remote Sensing 38 3.4 Data Collection Systems 41 vii viii CONTENTS 3.5 Errors, Artifacts, and Required Corrections 45 3.6 Processing 49 3.7 Implications for Storage and Access 61 3.8 Examples of Systems that Store or Provide Access to Remotely Sensed Data 66 3.9 Summary and Conclusion 77 3.10 Acknowledgments 78 References 78 Additional Reading 81 4 Medical Imagery 83 Stephen Wong and Kent Soo Hoo, Jr. 83 4.1 Introduction 83 4.2 Applications 85 4.3 Challenges 89 4.4 Enabling Technologies 95 4.5 Standards 98 4.6 Systems Integration 101 4.7 Conclusion 102 Appendix 103 References 103 5 Images in the Exploration for Oil and Gas 107 Peter Tilke 107 5.1 Introduction 107 5.2 Data Characteristics 108 5.3 Selected Application Scenarios 117 5.4 Enabling Technologies 125 5.5 Challenges and Open Problems 132 Appendix 132 References 137 STORAGE AND SYSTEM ARCHITECTURE 6 Storage Architectures for Digital Imagery 139 Harrick M. Vin 139 6.1 Storage Management 140 6.2 Fault Tolerance 145 6.3 Retrieval Techniques 149 6.4 Caching and Batching Issues 152 6.5 Architectural Issues 153 6.6 Conclusion 156 References 156 CONTENTS ix 7 Database Support for Multimedia Applications 161 Michael Ortega-Binderberger and Kaushik Chakrabarti 161 7.1 Introduction 161 7.2 A Model for Content-Based Retrieval 162 7.3 Overview of Current Database Technology 166 7.4 Image Retrieval Extensions to Commercial DBMSs 172 7.5 Current Research 186 7.6 Conclusion 203 Acknowledgments 204 References 204 8 Image Compression — A Review 211 Sheila S. Hemami 211 8.1 Introduction 211 8.2 Entropy — A Bound on Lossless Compression 213 8.3 Rate-Distortion Theory — Performance Bounds for Lossy Compression 215 8.4 Human Visual System Characteristics 217 8.5 Pixel-Based Redundancy Reduction 220 8.6 Quantization 227 8.7 Lossless Image-Compression Systems 230 8.8 Lossy Image-Compression Systems 231 8.9 Some Comments on JPEG-2000 236 8.10 Conclusion 237 References 237 9 Transmission of Digital Imagery 241 Jeffrey W. Percival 241 9.1 Introduction 241 9.2 Bulk Transmission of Raw Data 242 9.3 Progressive Transmission 243 9.4 Some Examples 251 9.5 Summary 258 References 258 INDEXING AND RETRIEVAL 10 Introduction to Content-Based Image Retrieval — Overview of Key Techniques 261 Ying Li and C.-C. Jay Kuo 261 10.1 Introduction 261 10.2 Feature Extraction and Integration 263 10.3 Similarity Functions 264 x CONTENTS 10.4 Feature Indexing 271 10.5 Interactive Content-Based Image Retrieval 272 10.6 The MPEG-7 Standard 276 10.7 Conclusion 278 References 279 11 Color for Image Retrieval 285 John R. Smith 285 11.1 Introduction 285 11.2 Color Descriptor Extraction 286 11.3 Color Descriptor Metrics 294 11.4 Retrieval Evaluation 300 11.5 Summary 308 References 309 12 Texture Features for Image Retrieval 313 B.S. Manjunath and Wei-Ying Ma 313 12.1 Introduction 313 12.2 Texture Features 316 12.3 Texture Features Based on Spatial-Domain Analysis 318 12.4 Autoregressive and Random Field Texture Models 321 12.5 Spatial Frequency and Transform Domain Features 323 12.6 Comparison of Different Texture Features for Image Retrieval 326 12.7 Applications and Discussions 329 12.8 Conclusion 339 Acknowledgments 339 References 339 13 Shape Representation for Image Retrieval 345 Benjamin B. Kimia 345 13.1 Introduction 345 13.2 Where Is Indexing by Shape Relevant? 346 13.3 Image Preparation and Query Formulation 348 13.4 Representation of Shape 349 13.5 Matching, Shape Similarity, and Validation 357 References 358 14 Multidimensional Indexing Structures for Content-Based Retrieval 373 Vittorio Castelli 373 14.1 Introduction 373 14.2 Feature-Level Image Representation 374 CONTENTS xi 14.3 Taxonomies of Indexing Structures 390 14.4 The Main Classes of Multidimensional Indexing Structures 391 14.5 Choosing an Appropriate Indexing Structure 396 14.6 Future Directions 398 Appendix 399 References 424 15 Multimedia Indexing 435 Christos Faloutsos 435 15.1 Introduction 435 15.2 Gemini: Fundamentals 437 15.3 1D Time Series 441 15.4 2D Color Images 447 15.5 Extension: Subpattern Matching 452 15.6 Conclusion 458 Appendix: Survey 459 References 460 16 Compressed or Progressive Image Search 465 Sethuraman Panchanathan 465 16.1 Introduction 465 16.2 Image Indexing in the Compressed Domain 466 16.3 Conclusion 492 16.4 Summary 492 Acknowledgment 493 References 493 17 Concepts and Techniques for Indexing Visual Semantics 497 Alejandro Jaimes and Shih-Fu Chang 497 17.1 Introduction 497 17.2 Indexing Visual Information at Multiple Levels 500 17.3 Content-Based Techniques and Object Recognition 510 17.4 Learning Visual Object Detectors: The Visual Apprentice 536 17.5 Conclusion and Future Directions 554 Appendix 555 References 556 Index 567 CONTRIBUTORS LAWRENCE D. BERGMAN, IBM T.J. Watson Research Center, 30 Saw Mill River Rd., Hawthorne, NY 10532 VITTORIO CASTELLI, IBM T.J. Watson Research Center, P.O. Box 128, York- town Heights, NY 10598 KAUSHIK CHAKRABARTI, University of California at Irvine, Information & Computer Science, 444 Computer Science Building, Irvine, CA 92697-3425 SHIH-FU CHANG, Columbia University, Department of Electrical Engineering, S.W. Mudd Building, Room 1312, New York, NY 10027 CARLO COLOMBO, Universita` Di Firenze, Dipartimento di Sistemi E Infor- matica, Via Santa Marta 3, 1-50139 Firenze, Italy ALBERTO DEL BIMBO, Universita` di Firenze, Dipartimento di Sistemi E Infor- matica, Via Santa Marta 3, 1-50139 Firenze, Italy CHRISTOS FALOUTSOS, Carnegie Mellon University, Department of Computer Science, Wean Hall, Pittsburgh, PA 15213-3891 SHEILA S. HEMAMI, Cornell University, School of Electrical Engineering, 332 Rhodes Hall, Ithaca, NY 14853 ALEJANDRO JAIMES, Columbia University, Department of Electrical Engi- neering, 500 West 120th Street, S.W. Mudd Bldg., Room 1312, New York, NY 10027 BENJAMIN B. KIMIA, Brown University, Department of Engineering, Barus and Holley 320, Box D, Providence, RI 02912 C.-C. JAY KUO, University of Southern California, Department of Electrical Engineering Systems, MC2564, Los Angeles, CA 90089-2564 YING LI, University of Southern California, Department of Electrical Engineering-Systems, EEB 400, Los Angeles, CA 90089 WEI-YING MA, Microsoft Research China, Beijing, China B.S. MANJUNATH, University of California at Santa Barbara, Department of Electrical and Computer Engineering, Santa Barbara, CA 93106-9560 xiii xiv CONTRIBUTORS SHARAD MEHROTRA, University of California at Irvine, Information & Computer Science, 444 Computer Science Building, Irvine, CA 92697-3425 MICHAEL ORTEGA-BINDERBERGER, University of Illinois, Department of Computer Science, Urbana-Champaign, IL SETHURAMAN PANCHANATHAN, Arizona State University, Department of Computer Sciences and Engineering, P.O. Box 875406, Tempe, AZ 85287- 5406 JEFFREY W. PERCIVAL, University of Wisconsin, Space Astronomy Laboratory, 6295 Chamberlain Hall, 1150 University Avenue, Madison, WI 53706 H.K. RAMAPRIYAN, Earth Science Data and Information System Project, Code 423 NASA, Goddard Space Flight Center, Greenbelt, MD 20771 PRASHANT SHENOY, University of Massachusetts, Department of Computer Science, Amherst, MA 01003-4610 JOHN R.
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