A dynamic and robust image processing based method for measuring the yarn diameter and its variation

Abstract

The yarn diameter is an effective property in determining fabric structure and processing settings. There are different systems of measuring the yarn diameter; among them is the image analysis of the yarn’s microscopic images. This method is considered to be more precise than other methods, but it is “static” in nature as it measures the property at scattered intervals and does not reflect the continuous variation of the yarn diameter. The goal of the current work is to measure the yarn diameter and its variation over a long length of yarn at fixed intervals to consider the “dynamic” change in the property. To achieve this goal, a high-speed camera (HSC) with a proper magnification was used to capture the images of the yarn and a new robust algorithm was developed to analyze the massive amount of yarn pictures in a reasonable time. The collected data for the yarn diameter were analyzed and compared to the results of the commercial Uster Evenness Tester IV. The results of the HSC were very comparable to the results of Uster and they were able to detect the short-term, the long-term, and the periodic variation of the yarn diameter.