@inproceedings{4b03b48646d14dff8ae531d66cd48449,
title = "Textile flaw detection using optimal Gabor filters",
abstract = "This study presents a new automatic and fast approach to design optimised Gabor filters for textile flaw detection applications. The defect detection problem is solved by using a semi-supervised approach. The aim is to automatically discriminate between {"}known{"} nondefective background textures and {"}unknown{"} defective textures. The parameters of the optimal 2-D Gabor filters are derived by constrained minimisation of a Fisher cost function. Such optimised Gabor filters are capable of detecting both, structural and tonal defects. This adaptable approach can detect a large variety of flaw types, while at the same time, accounting for their changing appearance in different texture backgrounds. When applied to a large database of textile fabrics, accurate detection with a low false alarm rate was achieved.",
keywords = "Unsupervised texture segmentation, Local defects",
author = "A Bodnarova and M Bennamoun and SJ Latham",
year = "2000",
language = "English",
isbn = "0-7695-0751-4",
series = "International Conference On Pattern Recognition",
publisher = "IEEE",
pages = "799--802",
editor = "A Sanfeliu and JJ Villanueva and M Vanrell and R Alquezar and J Crowley and Y Shirai",
booktitle = "15th International Conference On Pattern Recognition, Vol 4, Proceedings",
note = "15th International Conference on Pattern Recognition (ICPR-2000) ; Conference date: 03-09-2000 Through 07-09-2000",
}