IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Content-Based Image Retrieval Query Paradigms

Content-Based Image Retrieval Query Paradigms
View Sample PDF
Author(s): Colin C. Venters (University of Manchester, UK), Richard J. Hartley (Manchester Metropolitan University, UK) and William T. Hewitt (University of Manchester, UK)
Copyright: 2005
Pages: 8
Source title: Encyclopedia of Information Science and Technology, First Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-553-5.ch098

Purchase

View Content-Based Image Retrieval Query Paradigms on the publisher's website for pricing and purchasing information.

Abstract

The proliferation in volume of digital image data has exacerbated the general image retrieval problem, creating a need for efficient storage and flexible retrieval of vast amounts of image data (Chang, 1989). Whilst there have been significant technological advances with image data capture and storage, developments in effective image retrieval have not kept pace. Research in image retrieval has been divided into two areas: concept-based image retrieval and content-based image retrieval. The former focuses on the use of classification schemes or indexing terms to retrieve images while the latter focuses on the visual features of the image, such as colour, shape, texture, and spatial relationships.

Related Content

Adeyinka Tella, Oluwakemi Titilola Olaniyi, Aderinola Ololade Dunmade. © 2021. 24 pages.
Md. Maidul Islam. © 2021. 17 pages.
Peterson Dewah. © 2021. 23 pages.
Lungile Precious Luthuli, Thobekile K. Buthelezi. © 2021. 14 pages.
Delight Promise Udochukwu, Chidimma Oraekwe. © 2021. 13 pages.
Julie Moloi. © 2021. 18 pages.
Mandisa Msomi, Lungile Preciouse Luthuli, Trywell Kalusopa. © 2021. 17 pages.
Body Bottom