Feature tree clustering for image segmentation

Suguru Inoue, Masafumi Hagiwara

研究成果: Conference article

1 引用 (Scopus)

抜粋

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.

元の言語English
ページ(範囲)2022-2027
ページ数6
ジャーナルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
3
出版物ステータスPublished - 2001 12 1
イベント2001 IEEE International Conference on Systems, Man and Cybernetics - Tucson, AZ, United States
継続期間: 2001 10 72001 10 10

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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