Abstract:

For the problem of inspecting the levelness of dyed polyamide filaments, sample images of stockings are extracted by CCD camera, and Quotient image normalization method is proposed for the correction of optical source uniformity of the extracted stocking images, whose color feature processing is carried out by using the polynomial regression model. After processing, their mean/maximum color differences are 0.439/1.328 CIELAB units. Then color features of each sample are obtained via adopting hue percentage histogram of HSV color space algorithm. These features are regarded as input vectors for Fuzzy C-means clustering algorithm (FCM) through empirical equation. Finally, the color levelness rating of the stockings are automatically created by means of FCM. The experiment shows that the maximum number of iterations is 100, the bound of settle-out error is 1×10-5 , the fuzzy weighting index is 2, and the error between the experimental value and eye viewing result is 0.125% as showed when the single digits in the clustering center are 2、3、4、5 respectively. This error is far less than the permit error of production and technical standard.