An overview of Image Retrieval Systems using Relevance Feedback Method

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

The rapid development in the field of image processing system, image retrieval is the main thing to retrieve the desire method. During the past decades image data have been permanently increased leading to huge repositories. Now a day, numerous feature extraction methods have been processed to improve the quality of content-based image retrieval and image classification systems. In this paper, we are analyzing the technique of Relevance Feedback method for the purpose of image retrieval system. This overview offers a very useful study to all the methods used for color image retrieval system. The main aim of this paper is to develop a functional retrieval system which can be used in a wide variety of image retrieval applications.

References

1. Alaa Riad, Hamdy Elminir and Sameh Abd-Elghany, “Web Image Retrieval Search Engine based on Semantically Shared Annotation”, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 2, No 3, March 2012, ISSN (Online): 1694-0814, pp.223-228.

2. A. Arampatzis, K. Zagoris, and S.A. Chatzichristofis, “Dynamic two-stage image retrieval from large multimedia databases,” Information Processing & Management, vol. 49, 2013, pp. 274–285.

3. H. Chaudhari and D. Patil, “A Survey on Automatic Annotation and Annotation Based Image Retrieval,” International Journal of Computer Science and Information Technologies, vol. 5.2, 2014, pp. 1368–1371.

4. N. Chauhan and M. Goyani, “Enhanced Multistage Content Based Image Retrieval,” IJCSMC, vol. 2, Issue. 5, 2013, pp. 175–179.

5. KarishmaMutha and BelaJoglekar, “Image Retrieval Using Navigation Pattern for Relevance Feedback: A Survey”, Proc. of the Intl. Conf. on Advances in Computing and Communication – ICACC 2013, pp. 38-42.

6. Kranthi Kumar.K, T.Venu Gopal and M. Rama Krishna, “ Relevance Feedback For Content Based Image Retrieval Based On Multitexton Histogram And Microstructure Descriptor”, Publications Of Problems & Application In Engineering Research - Paper https://ijpaper.com/ CSEA2012 ISSN: 2230-8547; e-ISSN: 2230-8555, pp. 247-253.

7. Mohammed Alkhawlani, Mohammed Elmogy and Hazem El Bakry, “Text-based, Content-based, and Semantic-based Image Retrievals: A Survey”, International Journal of Computer and Information Technology (ISSN: 2279 – 0764) Volume 04 – Issue 01, January 2015, pp. 58-66.

8. Pushpa B. Patil and Manesh Kokare, “International Journal of Web & Semantic Technology (IJWesT)”, Vol.2, No.4, October 2011, pp. 139-148.

9. G. ThakoreDarshak "Evaluation enhancement development and implementation of content based image retrieval algorithms".PhDThesis.Maharaja Sayajirao University .2013.

10. X. Wang, S. Qiu, K. Liu, and X. Tang, “Web image re-ranking using query-specific semantic signatures,” IEEE, 2013.

Keywords

Image Retrieval system, Relevance Feedback method, Feature extraction, Image Processing.