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Image Retrieval: Information and Rough Set Theories

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Details

Original languageEnglish
Pages (from-to)631-637
Number of pages7
JournalProcedia Computer Science
Volume54
DOIs
Publication statusPublished - 2015
Publication typeA1 Journal article-refereed
Event11th International Conference on Communication Networks, ICCN 2015 - Bangalore, India
Duration: 21 Aug 201523 Aug 2015

Abstract

In 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.

ASJC Scopus subject areas

Keywords

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

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Field of science, Statistics Finland