Sequential fuzzy cluster extraction by a graph spectral method

Kohei Inoue, Kiichi Urahama

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

Sequential extraction method is presented for fuzzy clusters from a set of point data which is represented by a weighted graph. Nodes and links in the graph have nonnegative real weights. Memberships of data in a cluster are evaluated by the principal eigenvector of the weighted adjacency matrix of the graph. Node weights are successively reduced after extraction of clusters. The extraction of clusters is stopped when the volume of an extracted cluster reveals abrupt rebound. The method is applied to image segmentation and extraction of skin color regions from color images.

Original languageEnglish
Pages (from-to)699-705
Number of pages7
JournalPattern Recognition Letters
Volume20
Issue number7
DOIs
Publication statusPublished - Jul 1 1999

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Color
Image segmentation
Eigenvalues and eigenfunctions
Skin

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Cite this

Sequential fuzzy cluster extraction by a graph spectral method. / Inoue, Kohei; Urahama, Kiichi.

In: Pattern Recognition Letters, Vol. 20, No. 7, 01.07.1999, p. 699-705.

Research output: Contribution to journalArticle

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