Texture Classification Based on Topographic Image Structure

نویسندگان

  • Phongsuphap Sukanya
  • Ryo Takamatsu
  • Makoto Sato
چکیده

In this paper, we present a structural and statistical approach for texture classification. It can achieve with a higher accuracy rate comparing to the Spatial Gray Level Dependence (SGLD) method and Laws' method. Our method uses the previously proposed operator, the Surface-Shape operator (SS-operator), for describing topographic structure of texture images. The SS-operator describes shape of each pixel comparing with its neighbourhood in terms of topographical shapes such as hill, dale, ridge, valley, etc. Then, we use co-occurrence matrices, a statistical measure, to summarize the s ~ a t i a l distributions of such topographical shapes over the considered image to form texture features. This method yields good classifications of MIT vision textures.

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تاریخ انتشار 1996