A fabric defect image is characterized by its prirmitive properties as well as the spatial relationships between them. A gray level co-occurrence can be specified in a matrix of the relative frequencies with which two neighboring pixels separated by a distance occur on the image. By applying the co-occurrence matrix and gray relational analysis of the gray theory, we can extract characteristic values of a fabric defect image and classify defects to recognize common problems, including broken warps, broken wefts, holes, and oil stains. Gray relational analysis is also used to investigate correlations of the analyzed factors among the selected characteristic indicators in a randomized factor sequence through data processing. By justifying the most correlated defects, recognition accuracy can reach 94%.

This research aims to develop multifunctional polypropylene (PP) fiber with a far-infrared ray emission property and microorganism resistance. The processing parameters, including powder proportion, twin-screw mixing and melt spinning, were planned using the Taguchi method, gray relational analysis and the technique for order preference by similarity to ideal solution. The emission test results showed that the far-infrared ray emission value of composite fiber was 85%, which is 2.3 times that of pure PP. According to the far-infrared ray emission temperature rise test, the composite fiber temperature increases by 8.6℃, which is 43% higher than the 6℃ temperature rise of pure PP. The antibacterial test showed that the composite fiber has an antibacterial effect on staphylococcus aureus and pneumobacillus. Moreover, the composite fiber of PP with nano silicon dioxide and zinc oxide met the far-infrared ray emission property FTTS-FA-010 and qualitative antibacterial JIS L-1902 standards.

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