Existent industrial applications of computer vision systems ate directly connected to quality assurance requirements. The task of fabric defect detection is carried out by human visual inspection, in most of the traditional textile industry. The possibility of automated defect detection is investigated and a solution leading to improved productivity and high quality in the weaving process is proposed. We are introducing an unsupervised and robust system for the inspection of textured materials, based on multi-channel filtering. The Gabor function is employed for the filter bank and a cost function is used for filter selection. An appropriate thresholding of the filtered image followed by segmentation accomplishes the defect detection. Real image tests shows that our algorithm is robust and computationally efficient for the inspection of textured materials.
展开▼
