Unsupervised multiphase segmentation: A recursive approach

Kangyu Ni, Byung Woo Hong*, Stefano Soatto, Tony Chan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


We propose an unsupervised multiphase segmentation algorithm based on Bresson et al.'s fast global minimization of Chan and Vese's two-phase piecewise constant segmentation model. The proposed algorithm recursively partitions a region into two subregions, starting from the largest scale. The segmentation process automatically terminates and detects when all the regions cannot be partitioned further. The number of regions is not given and can be arbitrary. Furthermore, this method provides a full hierarchical representation that gives a structure of a given image.

Original languageEnglish (US)
Pages (from-to)502-510
Number of pages9
JournalComputer Vision and Image Understanding
Issue number4
StatePublished - Apr 1 2009


  • Active contour
  • Chan-Vese
  • Multiphase
  • Mumford-Shah
  • Scale-Space
  • Segmentation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition


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