Abstract
In this study, an image processing approach for the determination of yarn hairiness was presented. Yarn images taken under microscope were examined in MATLAB software. Seven different edge detection algorithms were used in order to separate the hairs from the yarn body accurately. Seven different textural properties of obtained yarn images were compared with Zweigle hairiness test results. The best hairiness results were obtained in Sobel and Prewitt edge detection methods. The findings have indicated that there were stronger correlation values for Sobel and Prewitt methods between Zweigle indices and four different textural features.
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