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

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...

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Bibliographic Details
Main Authors: Basturk, A., Ketencioglu, H., Yugnak, Z., Emin Yuksel, M.
Format: Conference Proceeding
Language:English
Subjects:
Fabrics
Feature extraction
Image analysis
Image texture analysis
Inspection
Principal component analysis
Singular value decomposition
Textiles
Wavelet analysis
Wavelet transforms
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Summary: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.
DOI:10.1109/ISSPA.2007.4555353