Content-based image retrieval is the set of techniques for retrieving relevant images from an image database on the basis of automatically derived image features. The need for efficient content-based image re trieval has increased tremendously in many application areas such as biomedicine, the military, commerce, education, and Web image clas sification and searching. In the biomedical domain, content-based im age retrieval can be used in patient digital libraries, clinical diagnosis, searching of 2-D electrophoresis gels, and pathology slides. I started my work on content-based image retrieval in 1995 when I was with Stanford University. The project was initiated by the Stan ford University Libraries and later funded by a research grant from the National Science Foundation. The goal was to design and implement a computer system capable of indexing and retrieving large collections of digitized multimedia data available in the libraries based on the media contents. At the time, it seemed reasonable to me that I should discover the solution to the image retrieval problem during the project. Experi ence has certainly demonstrated how far we are as yet from solving this basic problem.

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Authors and Affiliations

The Pennsylvania State University, USA

James Z. Wang

Bibliographic Information

Book Title: Integrated Region-Based Image Retrieval
Authors: James Z. Wang
Series Title: The Information Retrieval Series
DOI: https://doi.org/10.1007/978-1-4615-1641-5
Publisher: Springer New York, NY
eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2001
Hardcover ISBN: 978-0-7923-7350-6Published: 31 May 2001
Softcover ISBN: 978-1-4613-5655-4Published: 14 October 2012
eBook ISBN: 978-1-4615-1641-5Published: 06 December 2012
Series ISSN: 1871-7500
Series E-ISSN: 2730-6836
Edition Number: 1
Number of Pages: XIV, 178
Topics: Information Storage and Retrieval, Data Structures and Information Theory, The Computing Profession, Image Processing and Computer Vision

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Table of contents (9 chapters)

Front Matter

Back Matter

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