EMPIRICAL ANALYSIS OF CONTENTS BASED IMAGE RETRIEVAL USING GABOR FEATURE EXTRACTOR

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Published: Aug 28, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i7.4532
Keywords:
Content-based Image Retrieval (CBIR), Gabor feature, Euclidian Distance

Main Article Content

Ravinder Kumar
HMRITM, Affiliated with GGSIPU, DELHI
http://orcid.org/0000-0003-2117-5734
Brajesh Kr. Singh

Abstract

Due to increase in multimedia and internet technology day-by-day the Content Based Image Retrieval(CBIR) is an attractive research area for computer vision researcher since last decade. There is various model of CBIR have been proposed for retrieving images from huge database. In this work, we present an empirical analysis of CBIR model using Gabor feature descriptors in MATLAB. The similarity is measure by Euclidian distance method between query image and data base image. The efficiency of the CBIR Model can be calculating using both precision and recall and all the experimental results shows that system performs well on five different standard datasets.

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Vol. 8 No. 7 (2017): July-August 2017
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Author Biography

Ravinder Kumar, HMRITM, Affiliated with GGSIPU, DELHI

Ravinder Kumar received Ph. D. in IT from GGSIP University, Delhi in 2013 and M. Tech. degree in Computer Science & Engineering in 1998 from GJ University of Science and Technology, Hisar, India. Since 1999, he has been with the University School of ICT, GGSIP University, Delhi. Currently, he is Professor and Head, Department of CSE with HMR Institute of Technology and Management Delhi, India. His research interest is in the image processing and biometrics.

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