loading...
Statistical Landscape Features for Texture Classification
Cambridge UK August 23-August 26
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.133426217th International Conference on Patt ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Cun Lu Xu, Fudan Univ., Shanghai, P.R. China
Yan Qiu Chen, Fudan Univ., Shanghai, P.R. China
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.
Citation:
Cun Lu Xu, Yan Qiu Chen, "Statistical Landscape Features for Texture Classification," icpr, vol. 1, pp.676-679, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004
Usage of this product signifies your acceptance of the Terms of Use.