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Retrieval Architecture with Classified Query for Content Based Image Recognition


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

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.
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  • Retrieval Architecture with Classified Query for Content Based Image Recognition

Abstract Views: 109  |  PDF Views: 7

Authors

Rik Das
Department of Information Technology, Xavier Institute of Social Service, Ranchi, Jharkhand 834001, India
Sudeep Thepade
Department of Information Technology, Pimpri Chinchwad College of Engineering, Pune 411057, India
Subhajit Bhattacharya
Department of Marketing Management, Xavier Institute of Social Service, Ranchi, Jharkhand 834001, India
Saurav Ghosh
A.K. Choudhury School of Information Technology, University of Calcutta, Kolkata 700098, India

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.