DocumentCode :
2411675
Title :
Spatial texture analysis: a comparative study
Author :
Singh, Maneesha ; Singh, Sameer
Author_Institution :
Dept. of Comput. Sci., Exeter Univ., UK
Volume :
1
fYear :
2002
fDate :
2002
Firstpage :
676
Abstract :
In this paper we compare some of the traditional, and some fairly new, techniques of texture analysis on the MeasTex and VisTex benchmarks to illustrate their relative abilities. The methods considered include autocorrelation (ACF), co-occurrence matrices (CM), edge frequency (EF), Law´s masks (LM), run length (RL), binary stack method (BSM), texture operators (TO), and texture spectrum (TS). In addition, we illustrate the advantage of using feature selection on a combined set that improves the overall recognition performance.
Keywords :
feature extraction; image texture; object recognition; Law´s masks; MeasTex benchmark; VisTex benchmark; autocorrelation; binary stack method; co-occurrence matrices; edge frequency; feature selection; object recognition; recognition performance; run length; spatial texture analysis; texture operators; texture spectrum; Autocorrelation; Filter bank; Filtering; Fractals; Gabor filters; Image analysis; Image texture analysis; Signal processing algorithms; Statistics; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-1695-X
Type :
conf
DOI :
10.1109/ICPR.2002.1044843
Filename :
1044843
Link To Document :
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