Abstract:

Due to the foreign fibers types and characteristics of diversity, it was very difficult to construct a unified recognition model for eliminating raw cotton foreign fibers in cotton spinning enterprises processes. This paper proposes an image processing algorithm based on the cluster statistic analysis of cotton foreign fibers. The numerical statistical analysis was performed acquiring each component walues raw cotton fibers and the image information was divided into three categories by using RGB color image threshold statistical classification method. Then the foreign fibers was determined. Finally, by adopting image preprocessing for taking a better image and extracting the characteristics of foreign fibers in cotton, the area size, circumference and perimeter of foreign fibers were obtained. This should be the precondition for further eliminating raw cotton foreign fibers. The experimental results show that the algorithm can accurately identify foreign fibers.

Key words: foreign fiber, RGB color model, statistical classification, feature extraction