Study Of Method Of Reducing And Image Technology Detection Yarn Hairiness

During processing of textile, Yarn Hairiness is a significant indicator that reflects the quality of yarns. Yarn's lengths and quantities are directly related to the quality, grade and productivity of the products, and the smoothness of subsequent process. At present, the commonly used method for detecting yarn hairiness (including visual observation method, weight method and the projection method, etc.) have some shortcoming in the aspects of detective effect or price. The detective method of yarn hairiness which based on image technology can effectively overcome the deficiencies of conventional method and obtain scientific results.This paper has described the classification and indicators of the yarn hairiness and commonly used methods for detecting yarn hairiness, has introduced, analyzed and compared commonly used existing detective instruments of the yarn hairiness;This paper has described the forming mechanism of the yarn hairiness and its'influence on the textile production. This paper has proposed the methods and measures on reducing yarn hairiness in accordance with the forming mechanism of the yarn hairiness.Combined with the physical characteristics and shape features of the yarn hairiness, combined with the theory of the image analysis based on the detective method of the yarn hairiness in the traditional blackboard methods, the paper has presented the detective method of the hairiness with image processing technology.The detective process of the yarn hairiness is: first, inputs the obtained yarn image into computer firstly to get a sampling image; then transforms gray level, skew correction, noise reduction, edge sharpening and a series of preprocessing operations to sampling image to obtain a binary image that can reflect clearly the disposition of hairiness. Strengthen the edges of the yarn via using morphological operations. Finally, extracts the perimeter, area, shape factor and other characteristic parameters of the yarn from the edge map via using multi-region tracking to complete the automatic detection of yarn hairiness.With detecting yarn hairiness by using image processing technique, we can obtain intuitively the morphological characteristics of the hairiness, and get the quantities and index of the hairiness which has different length. This method is rapid, convenient and low cost. It has relieved the work strength of the artificial measurement, and improved the accuracy and efficiency of hairiness detection.