Feature tree clustering for image segmentation

Suguru Inoue, Masafumi Hagiwara

研究成果: Conference article査読

1 被引用数 (Scopus)


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.

ジャーナルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
出版ステータスPublished - 2001 12月 1
イベント2001 IEEE International Conference on Systems, Man and Cybernetics - Tucson, AZ, United States
継続期間: 2001 10月 72001 10月 10

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ハードウェアとアーキテクチャ


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