Publication Type:

Journal Article

Source:

Institute of Integrative Omics and Applied Biotechnology, Volume 7, Issue 3, p.11-18 (2016)

URL:

http://www.iioab.org/IIOABJ_7(3)/IIOABJ_7(3)11-18.pdf

Abstract:

Content Based Image Retrieval (CBIR) is an extensively used application in the field of Image Processing. It is used to search through a massive database and retrieve the images that have similarity with the query image. In this paper, performance is evaluated for Sparse Banded Filter matrices (ABfilter) against the standard edge detection filters through Content Based Image Retrieval. Performance factor of ABfilter directly relates to its edge detection capabilities. Here, edge detection followed by the Singular Value Decomposition (SVD) is done for feature extraction for both the query and images in database. Query image feature and database image features are matched and those having similar values are retrieved. Similarity measurement is done by computing the distance between corresponding features. Experimental results indicate that retrieval results using ABfilter is much better than using standard edge detection filters for the same, which in turn establishes its superiority in edge detection.

Cite this Research Publication

H. T. Suseelan, Sudhakaran, S., Sowmya V., and Dr. Soman K. P., “Performance Evaluation of Sparse Banded Filter Matrices using content based image retrieval”, Institute of Integrative Omics and Applied Biotechnology, vol. 7, no. 3, pp. 11-18, 2016.

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