期刊名称：International Journal of Computer Systems Science and Engineering
印刷版ISSN：1307-430X
出版年度：2008
卷号：04
期号：02
页码：171-171
出版社：World Academy of Science, Engineering and Technology
摘要：In the framework of adaptive parametric modelling of
images, we propose in this paper a new technique based on the
Chandrasekhar fast adaptive filter for texture characterization. An
Auto-Regressive (AR) linear model of texture is obtained by
scanning the image row by row and modelling this data with an
adaptive Chandrasekhar linear filter. The characterization efficiency
of the obtained model is compared with the model adapted with the
Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence
method features. The comparison criteria is based on the
computation of a characterization degree using the ratio of "betweenclass"
variances with respect to "within-class" variances of the
estimated coefficients. Extensive experiments show that the
coefficients estimated by the use of Chandrasekhar adaptive filter
give better results in texture discrimination than those estimated by
other algorithms, even in a noisy context.
Loading...
