基于Kirsch和Canny算子的陶瓷碗表面缺陷检测方法

Surface Defect Detection Method of Ceramic Bowl Based on Kirsch and Canny Operator

提出了一种基于机器视觉的陶瓷碗表面缺陷检测方法,该方法主要通过Kirsch算子和Canny算子的结合来实现表面缺陷的边缘检测。采用传统Kirsch算子的8个方向模板分别对图像上的每一个像素点进行卷积求导,选取最大模板,确定其边缘方向,结合Canny算子信噪比高、检测准确度高、边缘细节保留好等特点完成表面缺陷的检测,通过缺陷的几何特征判断是否存在缺陷。实验结果表明,该算法很好地抑制了噪声干扰,提高了边缘定位准确性及检测准确度,在保留边缘信息的同时避免了伪边缘的出现。

Based on machine vision, one method used for detecting the surface defects of ceramic bowls is proposed. This method is mainly used to accomplish the edge detection of surface defects by means of Kirsch operator in combination with Canny operator. It adopts the eight direction templates from the traditional Kirsch operator to calculate the derivative convolution of every pixel point, singles out the optimal template, and determines the edge direction. The high signal-to-noise ratio, high detection accuracy and edge detail keeping of the Canny operator are combined to accomplish the detection of surface defects. Whether there is a defect or not is determined based on the the geometric features of defects. Experimental results show that this new method can effectively suppress noise disturbance, improve the edge localization and detection accuracy, keep the edge information but simultaneously avoid the occurrence of false edges.