Feature tree clustering for image segmentation

Suguru Inoue, Masafumi Hagiwara

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

A new image segmentation method using a feature tree is proposed in this paper. The feature tree reflects the feature of an image. The proposed method is composed of two processes: (I) learning process and (II) clustering process. In the learning process, many efficient feature trees are made that construct a integrated tree. The integrated tree is used to segment images in the clustering process. Dividing an image is kept on from global point to local point. So, the proposed method can divide images considering not only the local property but also the global property. We applied the proposed method to some images, and obtained good results.

Original languageEnglish
Pages (from-to)2022-2027
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume3
Publication statusPublished - 2001 Dec 1
Event2001 IEEE International Conference on Systems, Man and Cybernetics - Tucson, AZ, United States
Duration: 2001 Oct 72001 Oct 10

Keywords

  • Feature tree
  • Image segmentation
  • Tree structure

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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