Table of Contents Author Guidelines Submit a Manuscript
Applied Computational Intelligence and Soft Computing
Volume 2016 (2016), Article ID 1861247, 9 pages
http://dx.doi.org/10.1155/2016/1861247
Research Article

Retrieval Architecture with Classified Query for Content Based Image Recognition

1Department of Information Technology, Xavier Institute of Social Service, Ranchi, Jharkhand 834001, India
2Department of Information Technology, Pimpri Chinchwad College of Engineering, Pune 411057, India
3Department of Marketing Management, Xavier Institute of Social Service, Ranchi, Jharkhand 834001, India
4A.K. Choudhury School of Information Technology, University of Calcutta, Kolkata 700098, India

Received 16 November 2015; Revised 31 January 2016; Accepted 2 February 2016

Academic Editor: Baoding Liu

Copyright © 2016 Rik Das et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The consumer behavior has been observed to be largely influenced by image data with increasing familiarity of smart phones and World Wide Web. Traditional technique of browsing through product varieties in the Internet with text keywords has been gradually replaced by the easy accessible image data. The importance of image data has portrayed a steady growth in application orientation for business domain with the advent of different image capturing devices and social media. The paper has described a methodology of feature extraction by image binarization technique for enhancing identification and retrieval of information using content based image recognition. The proposed algorithm was tested on two public datasets, namely, Wang dataset and Oliva and Torralba (OT-Scene) dataset with 3688 images on the whole. It has outclassed the state-of-the-art techniques in performance measure and has shown statistical significance.