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