Introduction to Query Techniques for Large CBIR Systems
Pravin D. Pardhi1, Prashant L. Paikrao2, Devendra S. Chaudhari3
1Pravin D. Pardhi, Electronics and Telecommunication Engineering, Government College of Engineering, Amravati, India.
2Prashant L. Paikrao, Electronics and Telecommunication Engineering, Government College of Engineering, Amravati, India.
3Devendra S. Chaudhari, Electronics and Telecommunication Engineering, Government College of Engineering, Amravati, India.
Manuscript received on February 15, 2012. | Revised Manuscript received on February 20, 2012. | Manuscript published on March 05, 2012. | PP: 181-184 | Volume-2 Issue-1, March 2012. | Retrieval Number: A0411022112/2012©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: Content-based image retrieval (CBIR) has received much research interest since couple of decades. The query technique for CBIR using relevance feedback is being used by the researchers, to search desired image from huge collection of visual data. This paper reviews various processes of image search and few query techniques.
Keywords: Content-based image retrieval (CBIR), image search, query technique, relevance feedback (RF).