Measuring the Geometrical Parameters of Slub Yarn Using a Computer Vision Based Image Sequencing Technique

Abstract

This article presents a computer vision method for measuring the geometrical parameters of slub yarn based on yarn sequence images captured from a moving slub yarn. An image segmentation method proposed by our earlier work was applied to segment sequence slub yarn images to obtain overlapping diameter data. Then an image stitching method was proposed to remove the overlapped data based on the normalised cross correlation (NCC) method. In order to detect the geometrical parameters of slub yarn, the frequency histogram , curve fitting, and spectrogram methods were adopted to analyse the sequence diameter data obtained. Four kinds of slub yarn with different geometrical parameters were tested using the method proposed and Uster method. The experimental results show that the detection results for slub amplitude, slub length, slub distance, and slub period obtained using the method proposed were consistent with the set values and Uster results.