Artificial Intelligence for Maximizing Content‐Based Image Retrieval

Marthie de Kock

Online Information Review

ISSN: 1468-4527

Article publication date: 27 November 2009

308

Keywords

Citation

de Kock, M. (2009), "Artificial Intelligence for Maximizing Content‐Based Image Retrieval", Online Information Review, Vol. 33 No. 6, pp. 1201-1202. https://doi.org/10.1108/14684520911011089

Publisher

:

Emerald Group Publishing Limited

Copyright © 2009, Emerald Group Publishing Limited


With the increase of multimedia – including images, audio and video, there is an urgent need for capturing, storing, retrieving, indexing, analysing and, summarising such data. The early image retrieval systems are based on manually annotated descriptions, called text‐based image retrieval (TBIR) systems. Content‐based image retrieval (CBIR) subsequently became an active and fast‐developing research area. CBIR aims to search images that are continually similar to the query based on visual content of the image in different ways without help of annotations. These systems are designed to support image retrieval as well as storage and processing activities related to image data management in multimedia information systems.

This book discusses aspects of CBIR using current technologies and applications within artificial intelligence (AI). It focuses on the following issues of AI for CBIR: AI for feature extraction and representation, AI for relevance feedback and intelligent CBIR systems and applications, and aiming at providing a single account of technologies and practices in AI for CBIR.

The book is divided into four major sections. The first section discusses the issues of AI for feature extraction and representation. The second section covers AI for distance measurement and image indexing and query. Section 3 deals with AI for relevance feedback, and Section 4 focuses on intelligent CBIR systems and applications. This book offers a theoretical perspective and practical solutions for academics, researchers and industry practitioners.

This publication is intended for academic and research libraries, as well as those involved in the study and design of intelligent agents. Researchers, practitioners, managers, educators and students seeking state‐of‐the‐art research and practice on the application of artificial intelligence will also benefit.

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