Image segmentation by histogram thresholding using hierarchical cluster analysis

Agus Zainal Arifin*, Akira Asano

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

182 Citations (Scopus)

Abstract

This paper proposes a new method of image thresholding by using cluster organization from the histogram of an image. A new similarity measure proposed is based on inter-class variance of the clusters to be merged and the intra-class variance of the new merged cluster. Experiments on practical images illustrate the effectiveness of the new method.

Original languageEnglish
Pages (from-to)1515-1521
Number of pages7
JournalPattern Recognition Letters
Volume27
Issue number13
DOIs
Publication statusPublished - 1 Oct 2006
Externally publishedYes

Keywords

  • Clustering
  • Image thresholding
  • Inter-class variance
  • Intra-class variance

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