descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2015 English Publisher:Elsevier BVJournal:Procedia Computer Science, volume 54, pages 631-637 (issn: 1877-0509,

Authors: Iftikhar Ahmad; Rama Murthy Garimella; Moncef Gabbouj;

doi: 10.1016/j.procs.2015.06.073

Image Retrieval: Information and Rough Set Theories

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Abstract

AbstractIn this research paper, we propose novel features based on information theory for image retrieval. We propose the novel concept of “probabilistic filtering”. We propose a hybrid approach for image retrieval that combines annotation approach with content based image retrieval approach. Also rough set theory is proposed as a tool for audio/video object retrieval from multi-media databases.

Related Organizations

Tampere University of Technology
Finland
Tampere University
Finland
International Institute of Information Technology, Hyderabad
India

Keywords

Hierarchical features, Normalized histogram, Image Retrieval., Roughset, K-L divergence

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