TY - GEN
T1 - A constrained minimisation approach to optimise Gabor filters for detecting flaws in woven textiles
AU - Bodnarova, A
AU - Bennamoun, M
AU - Latham, SJ
AU - Ieee, SIGNAL PROC SOC
AU - Ieee, SIGNAL PROC SOC
AU - Ieee, SIGNAL PROC SOC
PY - 2000
Y1 - 2000
N2 - Gabor filters have proved to be an effective segmentation and flaw detection tool. This study addresses the issue of an optimal 2-D Gabor filter design for automatically detecting defects in homogeneously textured woven fabrics. The parameters of these filters are derived through an optimisation process performing the minimisation of a Fisher cost function. Br constraining some of the Gabor filter parameters to specific values the aim is to optimise the filter to detect a certain type of flaw as it appears in a particular textile background. To account for the potentially large variety of flaw types, the optimal parameters for multiple sets of constraints are computed. The detection outcomes from each set of optimal filters are combined to produce a final classification result. Successful detection results (with low false alarm rates) suggest that this optimal Gabor filter approach is a promising method for automated detection of flaws in homogenous textiles.
AB - Gabor filters have proved to be an effective segmentation and flaw detection tool. This study addresses the issue of an optimal 2-D Gabor filter design for automatically detecting defects in homogeneously textured woven fabrics. The parameters of these filters are derived through an optimisation process performing the minimisation of a Fisher cost function. Br constraining some of the Gabor filter parameters to specific values the aim is to optimise the filter to detect a certain type of flaw as it appears in a particular textile background. To account for the potentially large variety of flaw types, the optimal parameters for multiple sets of constraints are computed. The detection outcomes from each set of optimal filters are combined to produce a final classification result. Successful detection results (with low false alarm rates) suggest that this optimal Gabor filter approach is a promising method for automated detection of flaws in homogenous textiles.
KW - Unsupervised texture segmentation
KW - Local defects
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=anu_research_portal_plus2&SrcAuth=WosAPI&KeyUT=WOS:000088999500903&DestLinkType=FullRecord&DestApp=WOS_CPL
M3 - Conference contribution
SN - 0-7803-6293-4
T3 - International Conference On Acoustics Speech And Signal Processing (icassp)
SP - 3606
EP - 3609
BT - 2000 Ieee International Conference On Acoustics, Speech, And Signal Processing, Proceedings, Vols I-vi
PB - IEEE
T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing
Y2 - 5 June 2000 through 9 June 2000
ER -