Intelligent Concept-Oriented and content-based image retrieval by using data mining and query decomposition techniques

S. Tseng, Ja Hwung Su, Hao Hua Ku, Bo Wen Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Traditional image retrieval based on visual-based matching is not effective in multimedia applications. Consequently, the modeling of high-level human sense for image retrieval has been a challenging issue over the past few years. In fact, the concepts hidden in the images play key roles in semantic image retrieval. In this paper, we propose a novel method named Intelligent Concept-Oriented Search (ICOS) that can capture the high-level concepts in images by utilizing data mining and query decomposition techniques. The contributions of the proposed method lie in that we provide: 1) effective annotation for conceptual objects, 2) association mining for conceptual objects, 3) visual ranking for conceptual objects and 4) intelligent search method for enhancing high-level concept image retrieval. Through experimental evaluations, ICOS is shown to be very effective and efficient in capturing the implicit high-level concepts for image retrieval.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings
Pages1273-1276
Number of pages4
DOIs
StatePublished - 23 Oct 2008
Event2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Hannover, Germany
Duration: 23 Jun 200826 Jun 2008

Publication series

Name2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings

Conference

Conference2008 IEEE International Conference on Multimedia and Expo, ICME 2008
CountryGermany
CityHannover
Period23/06/0826/06/08

Keywords

  • Concept-Oriented Search
  • Content-based image retrieval
  • Data mining
  • Query decomposition

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