The Application Of Image Recognition In Wool Fiber Detection

Although the figure of wool and cashmere are similar, their performance is great different. The price of cashmere is higher than that of wool because the warm capability of cashmere is better than wool' s, so that cashmere and wool are often interblended. In order to ensure product quality and manufacturer profits, it is urgent to find a method to distinguish them. Technician usually measures wool fiber' s diameter and squama' s length by hand. The technique is waste of time and energy, and the result is greatly affected by subject. What' s more, professional workers must be trained. As a result, it is stringent to need a measure system of detecting wool fiber. The measure of wool fiber diameter plays an important role in the system.The diameter measure of wool fiber magnified by optical microscope is mostly content of this paper. Wool fiber has very nice geometrical character. The image of wool fiber can be approximately regarded as parallel beelines in partial image. So we can measure wool fiber' s diameter by detecting parallel beelines. For exactly detecting parallel beelines in the wool fiber image, the following processes are adopted:1 Using Sobel edge detector to intensify edge.2 Using minimum error method .which belongs the global threshold , to attain binary image, so that background and object are distinguished.3 Deleting dot noise to reduce background noise in object and object noise in background.4 Thinning to discover wool fiber' s edge framework.5 Deleting small connected area.6 Using least-square technique to detect beeline, then calculating average wool fiber' s diameter based on the distance from point to beeline.