Title :
Defect detection in textured materials using optimized filters
Author :
Kumar, Ajay ; Pang, Grantham K H
Author_Institution :
Dept. of Comput. Sci., Hong Kong Univ. of Sci. & Technol., Clear Water Bay, China
fDate :
10/1/2002 12:00:00 AM
Abstract :
The problem of automated defect detection in textured materials is investigated. A new approach for defect detection using linear FIR filters with optimized energy separation is proposed. The performance of different feature separation criteria with reference to fabric defects has been evaluated. The issues relating to the design of optimal filters for supervised and unsupervised web inspection are addressed. A general web inspection system based on the optimal filters is proposed. The experiments on this new approach have yielded excellent results. The low computational requirement confirms the usefulness of the approach for industrial inspection.
Keywords :
FIR filters; automatic optical inspection; feature extraction; quality control; textile industry; automated defect detection; feature separation criterion; industrial inspection; linear FIR filters; low computational requirement; optimal filters; optimized energy separation; supervised web inspection; textured materials; unsupervised web inspection; Fabrics; Finite impulse response filter; Gabor filters; IIR filters; Information filtering; Information filters; Inspection; Production; Quality assurance; Textile industry;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2002.1033176