Terrain segmentation by structural texture discrimination

Antoni Grau; Joan Climent; Joan Aranda

doi:10.1117/12.331878

4 December 1998 Terrain segmentation by structural texture discrimination

Antoni Grau, Joan Climent, Joan Aranda

Proceedings Volume 3500, Image and Signal Processing for Remote Sensing IV; (1998) https://doi.org/10.1117/12.331878
Event: Remote Sensing, 1998, Barcelona, Spain

Abstract

In this work we present a new algorithm to generate the texture print of a region in an image. For this texture analysis, a texture print is found by means of counting the number of changes in the sign of the derivative in the gray level intensity function by rows and by columns, over a region with size N X N. These two histograms are represented as a unique string R of symbols. Therefore, a string-to-string correction problem as placement rules of elements (primitives) obtained statistically is used. In order to discriminate different texture regions a distance measure on strings based on minimum-cost sequences of edit operations is computed, this measure is the Leveshtein distance. The proposed algorithm is useful to discriminate between urban areas and rural areas due to the change in their textural aspect.

Citation Download Citation

Antoni Grau, Joan Climent, and Joan Aranda "Terrain segmentation by structural texture discrimination", Proc. SPIE 3500, Image and Signal Processing for Remote Sensing IV, (4 December 1998); https://doi.org/10.1117/12.331878

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