Evaluation method for yarn diameter unevenness based on image sequence processing

Abstract

This article proposes a testing and evaluation method for the unevenness of yarns based on measuring diameters of a series of testing points contained in the image sequence captured from a moving yarn. The address mapping table is used to achieve automatically measuring diameters of all testing points by fast addressing and locating their positions in the image sequence. Measuring the diameter of the testing point is based on the sub-image containing the testing point segmented from the captured image. In the yarn body extraction, according to the distribution character of gray-level projection, the sub-image is firstly divided into the yarn noumenon section, suspected noumenon section and image background section. Then the pixels of the suspected noumenon section are further categorized according to gray-level characters and connectivity to the yarn noumenon section. Finally, the complete yarn body image could be extracted. The diameter of the yarn testing point was represented by the average value of the neighboring point diameters in the axial direction. We compared the proposed method with the traditional measuring method by testing the same kind of yarn and performed an analysis using mathematical statistics methods. It proved that the proposed method can automatically process a continuous yarn image sequence and realize large sample statistics and unevenness evaluation.