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Proceedings Paper

Adaptive window-size selection approach for feature extraction in texture analysis
Author(s): Wen Sheng; Chenxi Xu; Jianguo Liu
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Paper 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.

Paper Details

Date Published: 21 September 2001
PDF: 6 pages
Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); doi: 10.1117/12.441456
Show Author Affiliations
Wen Sheng, Air Force Radar Academy (China)
Chenxi Xu, Air Force Radar Academy (China)
Jianguo Liu, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 4550:
Image Extraction, Segmentation, and Recognition
Tianxu Zhang; Bir Bhanu; Ning Shu, Editor(s)

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