Inspection of defects in fabrics using Gabor wavelets and principle component analysis

Author

Basturk, Alper ; Ketencioglu, Halil ; Yugnak, Zeki ; Yuksel, M. Emin

Author_Institution

Dept. of Comput. Eng., Erciyes Univ., Kayseri

fYear

2007

fDate

12-15 Feb. 2007

Firstpage

1

Lastpage

4

Abstract

In this paper, a new method for inspection of textile defects in fabrics is presented. The method is based upon the extraction of fabric features by Gabor wavelets. The Gabor wavelets transform provides an effective way to analyze images and extract features of textures. Principal component analysis using singular value decomposition is used to reduce the dimension of feature vectors. Performance of the method has been tested with defective fabric images taken from TILDA textile texture database. Experiments show that these defects are detected accurately.

Keywords

automatic optical inspection; fabrics; feature extraction; image texture; principal component analysis; production engineering computing; textile fibres; textile industry; wavelet transforms; Gabor wavelets; TILDA textile texture database; defects inspection; fabrics; features extraction; principle component analysis; singular value decomposition; textile defects; wavelets transform; Fabrics; Feature extraction; Image analysis; Image texture analysis; Inspection; Principal component analysis; Singular value decomposition; Textiles; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on

Conference_Location

Sharjah

Print_ISBN

978-1-4244-0778-1

Electronic_ISBN

978-1-4244-1779-8

Type

conf

DOI

10.1109/ISSPA.2007.4555353

Filename

4555353