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titleDefect Detection in Textile Fabric Images Using Wavelet Transforms and Independent Component Analysis
authorsA. Serdaroğlu, A. Ertüzün, A. Erçil
keywordsdefect, wavelet transformation, independent component analysis ICA, defect detection, textile fabric images, subband, basis vector, feature vector, Euclidean distance, feature extraction and detection, defect free,
abstractIn this paper, a new method based on the use of wavelet transformation prior to independent component analysis for solving the problem of defect detection in textile fabric images is presented. Different sub-bands of the wavelet packet tree scheme of the defect-free sub-windows are obtained and independent components of these subbands
are calculated as the basis vectors. The true feature vectors corresponding to these basis vectors are computed. The test sub-window is labeled as defective or not according to
the Euclidean distance between the true feature vector representing the non-defective regions and the feature vector of the sub-window under test. The advantage of adding wavelet analysis prior to independent component analysis is presented.
typeJournal Paper
journal7th International Conference on Pattern Recognition and Image Analysis
published year2007
serial1315
is_viewableyes
(Total records:1429)
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