castelli, bergman - image databases search and retriaval of digital imagery

[...]... (1996) Image Databases: Search and Retrieval of Digital Imagery Edited by Vittorio Castelli, Lawrence D Bergman Copyright  2002 John Wiley & Sons, Inc ISBNs: 0-4 7 1-3 211 6-8 (Hardback); 0-4 7 1-2 246 3-4 (Electronic) 2 Visible Image Retrieval CARLO COLOMBO and ALBERTO DEL BIMBO Universit´ di Firenze, Firenze, Italy a 2.1 INTRODUCTION The emergence of multimedia, the availability of large digital archives, and. .. part of the book is devoted to organizing, searching, and retrieving images Chapter 10 introduces the concept of content-based search Chapters 11, 12 and 13 discuss how to represent image content using low-level features (color, texture and shape, respectively) and how to perform feature-based similarity search Feature-based search is very expensive if the image repository is large, and the use of multidimensional... Databases: Search and Retrieval of Digital Imagery Edited by Vittorio Castelli, Lawrence D Bergman Copyright  2002 John Wiley & Sons, Inc ISBNs: 0-4 7 1-3 211 6-8 (Hardback); 0-4 7 1-2 246 3-4 (Electronic) 3 Satellite Imagery in Earth Science Applications H.K RAMAPRIYAN NASA, Goddard Space Flight Center, Greenbelt, Maryland 3.1 INTRODUCTION Remote sensing is the science of measuring characteristics of interest... for image management, Proceedings of the SPIE International Conference on Storage and Retrieval for Still Image and Video Databases, 1996 12 V.E Ogle and M Stonebraker, Chabot: retrieval from a relational database of images, IEEE Comput 28(9), 40–48 (1995) 13 P Alshuth et al., IRIS image retrieval for images and video, Proceedings of the First International Workshop on Image Database and Multimedia Search, ... using color, texture, and shape, Proc SPIE, Storage and Retrieval for Image and Video Databases, 1908, 173–187 (1993) 5 L.D Bergman, V Castelli, C.-S Li, and J.R Smith SPIRE, a digital library for scientific information, Special Issue of IJODL, “in the tradition of Alexandrian Scholars” 3(1), 85–99 (2000) 6 C.-S Li, P.S Yu, and V Castelli MALM, a framework for mining sequence databases at multiple abstraction... on the WWW with CBIR options highlight both an increasing interest in the use of digital imagery and the current limitations of general-purpose image search facilities This chapter reviews applications and research themes in visible image retrieval (VisIR), that is, retrieval by content of heterogeneous collections of single images generated with visible spectrum technologies It is generally agreed that... state of the art of content-based image retrieval systems and techniques 2.2 IMAGE RETRIEVAL AND ITS APPLICATIONS This section includes a critical discussion of the main limitations affecting current CBIR systems, followed by a taxonomy of VisIR systems and applications from the perspective of semantic requirements 2.2.1 Current Limitations of Content-Based Image Retrieval Semantic Gap Because of the... REFERENCES 1 R Chellappa, C.L Wilson, and S Sirohey, Human and machine recognition of faces: a survey, Proc IEEE 83(5), 705–740 (1995) 2 C.R Shyu et al., ASSERT: a physician-in-the-loop content-based retrieval system for HRCT image databases, Comput Vis Image Understand 75(1/2), 175–195 (1999) 3 E Binaghi, I Gagliardi, and R Schettini, Image retrieval using fuzzy evaluation of color similarity, Int J Pattern... purpose of studying visual iconography (see Section 2.4) State -of- the-art systems incorporating high-level semantics still require a huge amount of manual (and specifically textual) annotation, typically increasing with database size or task difficulty Web -Search Searching the web for images is one of the most difficult CBIR tasks The web is not a structured database — its content is widely heterogeneous and. .. Multimedia analysis and retrieval system (MARS) project, in P.B Heidorn and B Sandore, eds., Digital Image Access and Retrieval, 1997 15 W.-Y Ma and B.S Manjunath, NeTra: a toolbox for navigating large image databases, Multimedia Syst 7, 184–198 (1999) 16 R Picard, T.P Minka, and M Szummer, Modeling user subjectivity in image libraries, Proceedings of the IEEE International Conference on Image Processing . Image Databases: Search and Retrieval of Digital Imagery Edited by Vittorio Castelli, Lawrence D. Bergman Copyright  2002 John Wiley & Sons, Inc. ISBNs: 0-4 7 1-3 211 6-8 (Hardback); 0-4 7 1-2 246 3-4 . (1996). Image Databases: Search and Retrieval of Digital Imagery Edited by Vittorio Castelli, Lawrence D. Bergman Copyright  2002 John Wiley & Sons, Inc. ISBNs: 0-4 7 1-3 211 6-8 (Hardback); 0-4 7 1-2 246 3-4 . collections and trademarks. Chapter 3 is devoted to databases of remotely sensed images. Chapter 4 analyzes the different types of medical images, discusses standardization efforts, and 10 DIGITAL IMAGERY: