Efficient active contour and K-means algorithms in image segmentation

J. R. Rommelse*, H. X. Lin, T. F. Chan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

In this paper we discuss a classic clustering algorithm that can be used to segment images and a recently developed active contour image segmentation model. We propose integrating aspects of the classic algorithm to improve the active contour model. For the resulting CVK and B-means segmentation algorithms we examine methods to decrease the size of the image domain. The CVK method has been implemented to run on parallel and distributed computers. By changing the order of updating the pixels, it was possible to replace synchronous communication with asynchronous communication and subsequently the parallel efficiency is improved.

Original languageEnglish (US)
Pages (from-to)101-120
Number of pages20
JournalScientific Programming
Volume12
Issue number2
DOIs
StatePublished - Jan 1 2004
Externally publishedYes

Keywords

  • Active contour model
  • Clustering algorithm
  • Image segmentation
  • Level set functions
  • Synchronous and asynchronous communication

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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