An adaptive color image retrieval framework using gauss mixtures

Sangoh Jeong, Chee Sun Won, Robert M. Gray

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

2 Scopus citations

Abstract

To reduce the semantic gap, image retrieval systems based on users' relevance feedback have been adopted. However, since this structure needs human intervention during the retrieval process, it cannot be applied to fully automated systems. To avoid this problem, we propose a feed-forward framework instead of the feed-back retrieval system, which adds a classifier to the traditional system for giving feed-forward information to maximize the average precision. That is, given a database, our proposed system improves the overall precision by selecting the best mode based on known statistics (average precision vs. recall for each category). Lloyd-clustered Gauss mixtures are used in the classifier to provide the feed-forward category information and in the quantization of color images for histogram generation.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
Pages945-948
Number of pages4
DOIs
StatePublished - 2008
Event2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States
Duration: 12 Oct 200815 Oct 2008

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2008 IEEE International Conference on Image Processing, ICIP 2008
Country/TerritoryUnited States
CitySan Diego, CA
Period12/10/0815/10/08

Keywords

  • Adaptive
  • Color
  • Gauss mixtures
  • Image retrieval
  • Relevance feedback

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