Measurement of yarn apparent evenness based on modified Canny edge detection

Abstract

To evaluate accurately yarn apparent evenness, a simple yet effective method based on modified Canny edge detection was presented. Firstly, the originally captured yarn image is processed by Gaussian filtering, and the weighted least square method is used to calculate the horizontal and vertical directions of the image gradient for obtaining gradient images. Then the non-maximum suppression is applied to process the obtained gradient images and the double threshold algorithm is used to get the yarn edge curve. Finally, the average yarn diameter and the yarn coefficient variation (CV) of yarn were calculated via the number of pixels at the upper and lower edge points of the yarn evenness. To verify the validity and accuracy of the method, yarns with different linear densities were tested. The experimental results demonstrate that the proposed method can accurately detect the unevenness of the yarn apparent diameter.