A Study on Different Image Retrieval Techniques in Image Processing
Gulfishan Firdose Ahmed1, Raju Barskar2 

1Gulfishan Firdose Ahmed, Department of Information Technology, Maulana Azad National Institute of Technology, Bhopal (M.P.), India.
2Raju Barskar, Department of Computer Science and Engineering, University Institute of Technology, RGPV, Bhopal, (M.P.), India.
Manuscript received on August 22, 2011. | Revised Manuscript received on August 31, 2011. | Manuscript published on September 05, 2011. | PP: 247-251 | Volume-1 Issue-4, September 2011. | Retrieval Number: E0145081411/2011©BEIESP
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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: With the popularity of the network and development of multimedia technology, the traditional information retrieval techniques do not meet the users’ demand. Recently, the content-based image retrieval has become the hot topic and the techniques of content-based image retrieval have been achieved great development. In this paper, the basic components of content-based image retrieval system are introduced. Image retrieval methods based on color, texture, shape and semantic image are discussed, analyzed and compared. The semantic-based image retrieval is a better way to solve the “semantic gap” problem, so the semantic-based image retrieval method is stressed in this paper. Other related techniques such as relevance feedback and performance evaluation also discussed. In the end of paper the problems and challenges are proposed. In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. Many of these collections are the product of digitizing existing collections of analogue photographs, diagrams, drawings, paintings, and prints. Usually, the only way of searching these collections was by keyword indexing, or simply by browsing. Digital images databases however, open the way to content-based searching. In this paper we survey some technical aspects of current content-based image retrieval systems.
Keywords: Image retrieval, content-based image retrieval, color, texture, shape and semantic-based image retrieval.