Abstract:Aiming at the problem that the method of positioning the bottle bottom center is not accurate and the results for detecting the antiskid grain areas of bottom are unreliable, by taking advantage of the geometric features of antiskid grain areas on the bottom of the bottle, a localization algorithm based on variable weight random circle fitting the bottom is proposed in the paper. First, the bottom center is quickly prepositioned by gravity method, then the random variable weight circle fitting method is used to realize the precise positioning. Finally, the suspected defect region of the bottle bottom image is detected, and area, contour length, average gray, gray variance and circularity are extracted, then the support vector machine is used for classification and the defect is detected. The experiment results show that the positioning error of this method is less than 6 pixels, and the detect accuracy is 92.7%. It basically meets the actual production requirements.
