Title: Content-based image retrieval using SVD-based Eigen images

Authors: Naushad Varish; Arup Kumar Pal

Addresses: Department of Computer Science and Engineering, Indian School of Mines, Dhanbad, Jharkhand 826004, India ' Department of Computer Science and Engineering, Indian School of Mines, Dhanbad, Jharkhand 826004, India

Abstract: In this paper, a content-based image retrieval scheme using the singular value decomposition (SVD) is proposed where the feature vector was estimated from the selected significant components of a singular value decomposed image. The Eigen values of the decomposed image are divided into several numbers of groups and from each group we have constructed several Eigen images and subsequently, statistical values like mean, standard deviation and entropy are computed from those Eigen images. The constructed Eigen images are suitable to analyse the original image data in various image planes. This approach is applied to each colour components for formation of colour-based final feature vector. This approach is appropriate to reduce the overall processing cost in image retrieving process due to the consideration of significant image feature in SVD domain. The scheme is tested on a standard Corel image database and satisfactory results are achieved.

Keywords: content based image retrieval; CBIR; F-score; precision recall; SVD; singular value decomposition; statistical parameters; feature extraction.

DOI: 10.1504/IJIM.2016.079117

International Journal of Image Mining, 2016 Vol.2 No.1, pp.68 - 83

Received: 07 Sep 2015
Accepted: 02 Apr 2016

Published online: 13 Sep 2016 *

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