Fabric defect segmentation using multichannel blob detectors

The problem of automated defect detection in textured mate- rials is investigated. A new algorithm based on multichannel filtering is presented. The texture features are extracted by filtering the acquired image using a filter bank consisting of a number of real Gabor functions, with multiple narrow spatial frequency and orientation channels. For each image, we propose the use of image fusion to multiplex the infor- mation from sixteen different channels obtained in four orientations. Adaptive degrees of thresholding and the associated effect on sensitivity to material impurities are discussed. This algorithm realizes large com- putational savings over the previous approaches and enables high- quality real-time defect detection. The performance of this algorithm has been tested thoroughly on real fabric defects, and experimental results have confirmed the usefulness of the approach. © 2000 Society of Photo- Optical Instrumentation Engineers. (S0091-3286(00)01912-7)

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