New approach to parallel clustering and its application to image segmentation

Doron Hershfinkel, Its'hak Dinstein

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

Abstract

The proposed parallel clustering technique performs several clustering processes (for the same data set) in parallel, using different sets of initial cluster centers. Each clustering process consists of a sequence of iterations. The clustering processes are iterated in parallel within each parallel step. By the end of each parallel step, the clustering parameters are evaluated according to prespecified criteria. 'Non-promising' cluster center sets are discarded, and new cluster center sets are formed using 'promising' cluster centers. The presented illustrated examples indicate a reduction of 7% to 30% in the number of iterations required for convergence.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherPubl by Int Soc for Optical Engineering
Pages362-371
Number of pages10
ISBN (Print)0819410276
StatePublished - 1 Jan 1993
EventIntelligent Robots and Computer Vision XI: Biological, Neural Net, and 3-D Methods - Boston, MA, USA
Duration: 18 Nov 199220 Nov 1992

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume1826
ISSN (Print)0277-786X

Conference

ConferenceIntelligent Robots and Computer Vision XI: Biological, Neural Net, and 3-D Methods
CityBoston, MA, USA
Period18/11/9220/11/92

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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