A Hybrid Approach for content based image retrieval from large Dataset

International Journal of Computer Trends and Technology (IJCTT)          
© 2015 by IJCTT Journal
Volume-23 Number-1
Year of Publication : 2015
Authors : Devendra Kurwe, Prof. Anjna Jayant Deen, Dr. Rajeev Pandey


Devendra Kurwe, Prof. Anjna Jayant Deen, Dr. Rajeev Pandey "A Hybrid Approach for content based image retrieval from large Dataset". International Journal of Computer Trends and Technology (IJCTT) V23(1):16-21, May 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Image processing is one of the methods to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it. The volume of digital images generated and uploaded on the internet are very large. The major problem is retrieving the desired images from huge collection of images. To improve the retrieval performance an accurate and efficient system is required. Content based image retrieval technique has been a very useful system. Today content based image retrieval is a required concept, while dealing with multiple activities daily today either with computer or web or mobile we often need to query the database to find efficient required output in short time. In this paper we are proposing a hybrid approach which is the combination of genetic and Bayesian algorithm which giving us the better results in some aspects which overcomes the disadvantages of the existing algorithm and find its suitable in point of efficiency and accuracy. For the valuation of result two standard parameters one is Recall and another is Precision are used which shows better value in comparing to other retrieval algorithms.

1. Zhong Su, Hongjiang Zhang, Stan Li, and Shaoping Ma “Relevance Feedback in Content-Based Image Retrieval: Bayesian Framework, Feature Subspaces, and Progressive Learning” IEEE Transactions On Image Processing, August 2003
2. Sumaira Muhammad Hayat Khan, Dr.Ayyaz Hussain and Dr.Imad Fakhri Taha Alshaikhli “Comparative study on Content-Based Image Retrieval (CBIR)” International Conference on Advanced Computer Science Applications and Technologies, 2012.
3. Chih-Chin Lai and Ying-Chuan Chen “A User- Oriented Image Retrieval System Based on Interactive Genetic Algorithm” IEEE Transactions On Instrumentation And Measurement, October 2011
4. Prachi Bhende and Prof. A. N. Cheeran “Content Based Image Retrieval in Medical Imaging” International Journal of Computational Engineering Research.
5. Mohd. Danish, Ritika Rawat and Ratika Sharma “A Survey: Content Based Image Retrieval Based On Color, Texture, Shape & Neuro Fuzzy” International Journal of Engineering Research and Applications, September 2013.
6. Khlifia Jayech and Mohamed Ali Mahjoub “New approach using Bayesian Network to improve content based image classification systems” IJCSI International Journal of Computer Science Issues, November 2010
7. Nidhi Singhai and Prof. Shishir K. Shandilya “A Survey On: Content Based Image Retrieval Systems” International Journal of Computer Applications, July 2010.
8. Ritika Hirwane “Fundamental of Content Based Image Retrieval” International Journal of Computer Science and Information Technologies, (2012).
9. Neha Jain, Sumit Sharma and Ravi Mohan Sairam “Content Base Image Retrieval using Combination of Color, Shape and Texture Features” International Journal of Advanced Computer Research, March 2013.
10. Amanbir Sandhu and Aarti Kochhar” Content Based Image Retrieval using Texture, Color and Shape for Image Analysis” International Journal of Computers & Technology, AUG 2012.
11. Hatice Cinar Akakin and Metin N. Gurcan “Content-Based Microscopic Image Retrieval System for Multi-Image Queries” IEEE Transactions On Information Technology In Biomedicine, July 2012.
12. Mr. S. Manoharan and Dr. S. Sathappan” a novel approach for content based image retrieval using hybrid filter techniques” International Conference on Computer Science & Education, April 2013.
13. Nishant Singh, ShivRam Dubey, Pushkar Dixit, Jay Prakash Gupta” Semantic Image Retrieval by Combining Color, Texture and Shape Features” International Conference on Computing Sciences, (2012).
14. S.R.Surya, G.Sasikala “An Enhanced Image Retrieval using Contribution-based Clustering Algorithm with Spatial Feature of Texture Primitive and Edge Detection” International Journal of Computer Applications (0975 – 8887) August 2012.
15. Erchan Aptoula and Sebastien Lefevre “Morphological Description of Color Images for Content-Based Image Retrieval” IEEE Transactions on Image Processing, vol. 18, no. 11, November 2009.
16. Mahmoud R. Hejazi, Yo-Sung Ho” An Efficient Approach to Texture-Based Image Retrieval” Gwangju Institute of Science and Technology, 15 October 2007.

CBIR, Bayesian algorithm, Genetic algorithm, Feature Extraction.