An automatic segmentation technique for color images based on SOFM neural network

Jun Zhang, Jinglu Hu

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

In this paper, an automatic segmentation method based on self-organizing feature map (SOFM) neural network (NN) is presented for color images. First, a binary tree clustering procedure is used to cluster the colors in an image. In each node of the tree, a SOFM NN is used as a classifier which is fed by image color values. The output neurons of the SOFM NN define the color classes for each node. In our method, the number of color classes for each node is two. For each node of the tree, Hotelling transform based splitting condition is used to define if the current color classes should be split. To speed up the entire algorithm, a nearest neighbor interpolation is used to get the small training set for SOFM NN. Once the colors in an image are clustered, it is easy to segment a target by analyzing the color feature in an image. The method is independent of the color scheme, so it is applicable to any type of color images. Our experimental results show the validity of the proposed method.

本文言語English
ホスト出版物のタイトル2009 International Joint Conference on Neural Networks, IJCNN 2009
ページ3528-3533
ページ数6
DOI
出版ステータスPublished - 2009
イベント2009 International Joint Conference on Neural Networks, IJCNN 2009 - Atlanta, GA, United States
継続期間: 2009 6 142009 6 19

出版物シリーズ

名前Proceedings of the International Joint Conference on Neural Networks

Conference

Conference2009 International Joint Conference on Neural Networks, IJCNN 2009
国/地域United States
CityAtlanta, GA
Period09/6/1409/6/19

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

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