Unsupervised segmentation of texture images using feature selection

Yoshimasa Karino, Shinichiro Omachi, Hirotomo Aso

Research output: Contribution to journalArticlepeer-review


Highly precise segmentation of texture images is a technique which is indispensable in image understanding and image recognition. This paper proposes a method which represents the features of the texture image by using the wavelet transform, the nonlinear transformation, and a Gaussian filter, which are used in time-frequency analysis. A highly precise segmentation procedure for texture images is presented in which a feature suited to segmentation is selected from among a number of features. The usefulness of the proposed method is demonstrated through experiments using artificial data, and a result for a natural image is presented as an application to a real problem.

Original languageEnglish
Pages (from-to)58-66
Number of pages9
JournalElectronics and Communications in Japan, Part II: Electronics (English translation of Denshi Tsushin Gakkai Ronbunshi)
Issue number9
Publication statusPublished - 2005 Sept


  • Segmentation
  • Texture
  • Wavelet transform feature selection


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