DocumentCode :
1742341
Title :
Autocovariance-based perceptual textural features corresponding to human visual perception
Author :
Abbadeni, Noureddine ; Ziou, Djemel ; Wang, Shengrui
Author_Institution :
Fac. des Sci., Sherbrooke Univ., Que., Canada
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
901
Abstract :
It has been shown that humans use some perceptual textural features such as coarseness, contrast and direction to distinguish between textured images or regions. The aim of this paper is to present a new method to estimate these perceptual textural features using the autocovariance function. Computational measures derived from the autocovariance function to estimate these perceptual textural features are presented. Experimental results are then given and the correspondence between the computational measures proposed and the psychological measures is shown using some psychometric method
Keywords :
covariance analysis; human factors; image texture; visual perception; autocovariance function; autocovariance-based perceptual textural features; coarseness; computational measures; contrast; direction; human visual perception; psychological measures; psychometric method; textured images; textured regions; Computational modeling; Gradient methods; Humans; Image classification; Image retrieval; Image texture analysis; Pattern recognition; Psychology; Testing; Visual perception;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
ISSN :
1051-4651
Print_ISBN :
0-7695-0750-6
Type :
conf
DOI :
10.1109/ICPR.2000.903689
Filename :
903689
Link To Document :
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