Statistical Landscape Features for Texture Classification

Authors:
Cun Lu Xu;Yan Qiu Chen
Affiliations:
Fudan Univ., Shanghai, P.R. China;Fudan Univ., Shanghai, P.R. China
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Year:
2004

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Cited 2

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Texture analysis and classification using shortest paths in graphs

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Abstract

This paper proposes the use of information derived from the graph of a texture image function for texture description. The graph of an image function is a rumpled surface in the three-dimensional space that appears like a landscape. Four novel texture feature curves are used to characterize the texture. This method is named Statistical Landscape Features (SLF). SLF achieves a very high correct classification rate of 94.53% on the entire Brodatz set. Besides the very good performance, another remarkable advantage of the proposed method is that it has no parameter to tune.