Image segmentation by changing template block by block

C. F. Sin, Chi Kin Leung

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

In this paper, an entropy-based image segmentation method is proposed to segment a gray-scale image. The method starts with an arbitrary template. An index called Gray-scale Image Entropy (GIE) is employed to measure the degree of resemblance between the template and the underlying true scene that gives rise to the gray-scale image. The classification status of a block of pixels in the template is modified in a way to maximize the GIE. By repeatedly processing all blocks of pixels until a termination condition is met, the template would be changed to a configuration that closely resembles the true scene. This optimum template (in an entropy sense) is taken to be the desired segmented image. Investigation results from simulation study and the segmentation of practical images demonstrate the feasibility of the proposed method.
Original languageEnglish
Title of host publicationIEEE Region 10 International Conference on Electrical and Electronic Technology
Pages302-305
Number of pages4
Publication statusPublished - 1 Dec 2001
EventIEEE Region 10 International Conference on Electrical and Electronic Technology - Singapore, Singapore
Duration: 19 Aug 200122 Aug 2001

Conference

ConferenceIEEE Region 10 International Conference on Electrical and Electronic Technology
CountrySingapore
CitySingapore
Period19/08/0122/08/01

Keywords

  • Maximum entropy
  • Segmentation
  • Template matching
  • Thresholding

ASJC Scopus subject areas

  • Engineering(all)

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