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Histogram Generation from the HSV Color Space

Histogram Generation from the HSV Color Space
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Author(s): Shamik Sural (Indian Institute of Technology, Kharagpur, India), A. Vadivel (Indian Institute of Technology, Kharagpur, India) and A. K. Majumdar (Indian Institute of Technology, Kharagpur, India)
Copyright: 2005
Pages: 5
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.ch235

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Abstract

Digital image databases have seen an enormous growth over the last few years. However, since many image collections are poorly indexed or annotated, there is a great need for developing automated, content-based methods that would help users to retrieve images from these databases. In recent times, a lot of attention has been paid to the management of an overwhelming accumulation of rich digital images to support various search strategies. In order to improve the traditional text-based or SQL (Structured Query Language)-based database searches, research has been focused on efficient access to large image databases by the contents of images, such as color, shape, and texture. Content-based image retrieval (CBIR) has become an important research topic that covers a large number of domains like image processing, computer vision, very large databases, and human computer interaction (Smeulders, Worring, Santini, Gupta & Jain, 2000). Several content-based image retrieval systems and methods have recently been developed.

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