Adaptive window-size selection approach for feature extraction in texture analysis

Wen Sheng; Chenxi Xu; Jianguo Liu

doi:10.1117/12.441456

21 September 2001 Adaptive window-size selection approach for feature extraction in texture analysis

Wen Sheng, Chenxi Xu, Jianguo Liu

Proceedings Volume 4550, Image Extraction, Segmentation, and Recognition; (2001) https://doi.org/10.1117/12.441456
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

In texture analysis, the selection of window size has great influence on effectiveness of extracted feature and computing speed. This paper employs Gauss-markov random field (GMRF) model to describe textures, the least square error approach is employed to estimate field parameters, and it has been proved to be non-bias. Because there may be no solution by the estimation expression, a modification to it is presented. Based on the non-bias characteristic of parameter estimation, we present a window size selection approach for texture primitives, and experiment shows that our approach is very effective.

Citation Download Citation

Wen Sheng, Chenxi Xu, and Jianguo Liu "Adaptive window-size selection approach for feature extraction in texture analysis", Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); https://doi.org/10.1117/12.441456

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