An unsupervised segmentation framework for texture image queries

S. C. Chen, M. L. Shyu, C. Zhang

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

In this paper, a novel unsupervised segmentation frame-work for texture image queries is presented. The proposed framework consists of an unsupervised segmentation method for texture images, and a multi-filter query strategy. By applying the unsupervised segmentation method on each texture image, a set of texture feature parameters for that texture image can be extracted automatically. Based upon these parameters, an effective multi-filter query strategy which allows the users to issue texture-based image queries is developed. The test results of the proposed framework on 318 texture images obtained from the MIT VisTex and Brodatz database are presented to show its effectiveness.

Original languageEnglish (US)
Pages (from-to)569-573
Number of pages5
JournalProceedings - IEEE Computer Society's International Computer Software and Applications Conference
StatePublished - Jan 1 2001
Externally publishedYes
Event25th Annual International Computer Software and Applications Conference (COMPSAC)2001 - Chicago, IL, United States
Duration: Oct 8 2001Oct 12 2001

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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