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Texture image classification and segmentation using RANK-order clustering

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2 Author(s)
D. Patel ; Dept. of Electr. Eng. & Electron., Brunel Univ., Uxbridge, UK ; T. J. Stonham

Image analysis using texture as a spatial feature can be employed to segment regions of a complex scene or in the classification of surface materials. The relationship between most textural images and their description is mathematically intractable. In this paper the authors propose a new statistical measure, which is not based on a pre-defined formulation. Here, the local information in all directions around a pixel and its neighbourhood is represented in a `directional RANK-strength' vector. The proposed method leads to texture classification and segmentation methods. Both algorithms have been tested on natural images with results in agreement with perceived ones

Published in:

Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,

Date of Conference:

30 Aug-3 Sep 1992