Textile flaw detection using optimal Gabor filters

A Bodnarova, M Bennamoun, SJ Latham

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.
Original languageEnglish
Title of host publication15th International Conference On Pattern Recognition, Vol 4, Proceedings
EditorsA Sanfeliu, JJ Villanueva, M Vanrell, R Alquezar, J Crowley, Y Shirai
PublisherIEEE
Pages799-802
Number of pages4
ISBN (Print)0-7695-0751-4
Publication statusPublished - 2000
Event15th International Conference on Pattern Recognition (ICPR-2000) - BARCELONA, Spain
Duration: 3 Sept 20007 Sept 2000

Publication series

NameInternational Conference On Pattern Recognition

Conference

Conference15th International Conference on Pattern Recognition (ICPR-2000)
Country/TerritorySpain
CityBARCELONA
Period3/09/007/09/00

Fingerprint

Dive into the research topics of 'Textile flaw detection using optimal Gabor filters'. Together they form a unique fingerprint.

Cite this