A Proposed Method for Image Retrieval using Histogram values and Texture Descriptor Analysis
Wasim Khan1, Shiv Kumar2, Neetesh Gupta3, Nilofar Khan4

1Wasim Khan is with the Technocrats Institute of Technology Bhopal, (M.P.), India.
2Shi Kumar is with the Technocrats Institute of Technology, Bhopal, (M.P.), India.
3Neetesh Gupta is with the Technocrats Institute of Technology Bhopal, (M. P.), India.
4Nilofar Khan is with the Chameli Devi Group of Institutions, Indore, (M. P.), India.
Manuscript received on April 19, 2011. | Revised Manuscript received on April 29, 2011. | Manuscript published on May 05, 2011. | PP: 33-36 | Volume-1 Issue-2, May 2011. | Retrieval Number: A021031211
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Color and Texture information have been the primitive image descriptors in content based image retrieval systems. In this article, a method is proposed for image mining based on analysis of color Histogram values and texture descriptor of an image. For this purpose, three functions are used for texture descriptor analysis such as entropy, local range and standard deviation. To extract the color properties of an image, histogram values are used. The combination of the color and texture features of the image provides a robust feature set for image retrieval.
Keywords: Content-based image retrieval, color histogram, image texture.