A Hybrid Approach for content based image retrieval from large Dataset

  IJCTT-book-cover
 
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
  10.14445/22312803/IJCTT-V23P104

MLA

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.

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Keywords
CBIR, Bayesian algorithm, Genetic algorithm, Feature Extraction.