DocumentCode :
1705359
Title :
Texture inspection with self-adaptive convolution filters
Author :
Dewaele, P. ; Van Gool, L. ; Wambacq, A. ; Oosterlinck, A.
Author_Institution :
Catholic Univ. of Leuven, Belgium
fYear :
1988
Firstpage :
56
Abstract :
A resolution-independent method for detection of imperfections in quasi-periodic textures is described. After image standardization, the period is estimated in the horizontal and vertical directions. This determines the size of a sparse convolution mask. Mask coefficients are determined by the well-known technique of eigenfilter extraction. The method thus offers a completely automated generation of a bank of suitable filters, the form and the coefficients of which are made dependent on the texture type to be inspected. After feature extraction in the filtered images, a Mahalanobis classifier is applied
Keywords :
adaptive filters; eigenvalues and eigenfunctions; filtering and prediction theory; pattern recognition; picture processing; Mahalanobis classifier; eigenfilter extraction; feature extraction; flaw detection; image standardization; mask coefficients; pattern detection; picture processing; quasi-periodic textures; resolution-independent method; self-adaptive convolution filters; sparse convolution mask; texture inspection; Convolution; Fabrics; Feature extraction; Filter bank; Frequency domain analysis; Image edge detection; Inspection; Pattern analysis; Pixel; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1988., 9th International Conference on
Conference_Location :
Rome
Print_ISBN :
0-8186-0878-1
Type :
conf
DOI :
10.1109/ICPR.1988.28171
Filename :
28171
Link To Document :
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