Looking beyond region boundaries: A robust image similarity measure using fuzzified region features

Yixin Chen, James Z. Wang

Research output: Contribution to conferencePaper

3 Scopus citations

Abstract

The performance of most region-based image retrieval systems depend critically on the accuracy of object segmentation. We propose a region matching approach, unified feature matching (UFM), which greatly increases the robustness of the retrieval system against segmentation related uncertainties. In our retrieval system, an image is represented by a set of segmented regions each of which is characterized by a fuzzy feature reflecting color, texture, and shape properties. The resemblance between two images is then defined as the overall similarity between two families of fuzzy features, and quantified by the UFM measure. The system has been tested on a database of about 60,000 general-purpose images. Experimental results demonstrate improved accuracy and robustness.

Original languageEnglish (US)
Pages1165-1170
Number of pages6
StatePublished - Jul 11 2003
EventThe IEEE International conference on Fuzzy Systems - St. Louis, MO, United States
Duration: May 25 2003May 28 2003

Other

OtherThe IEEE International conference on Fuzzy Systems
CountryUnited States
CitySt. Louis, MO
Period5/25/035/28/03

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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  • Cite this

    Chen, Y., & Wang, J. Z. (2003). Looking beyond region boundaries: A robust image similarity measure using fuzzified region features. 1165-1170. Paper presented at The IEEE International conference on Fuzzy Systems, St. Louis, MO, United States.