一种改进的Canny算子在机器人视觉系统中的应用

在对传统Canny边缘检测算子深入分析的基础上，利用统计原理研究和分析图像灰度值数据，提出一种改进型Canny算子.与传统的Canny边缘检测算子相比，改进型的Canny算子将边缘点邻域内灰度相似的像素点的灰度平均值代替原灰度值，并引进一种自适应的阈值确定方法，根据灰度值信息确定高低阈值，在保持边缘提取准确性的同时增加了双阈值设置的自适应性.最后将改进型的Canny算子应用于工业机器人视觉系统中，并与传统的Canny算子的实验结果进行比对分析.实验结果表明，改进型的Canny算子更好的权衡了噪声和边缘之间的关系，对待测物体的边缘提取效果更好.

Improved Canny Operator in the Application of Robot Vision System

An improved Canny operator is proposed through researching and analyzing the data of the grey image with statistical principle on the basis of deep analysis of traditional Canny edge detection operator. Compared with the traditional Canny edge detection operator, improved Canny operator replaces the original grey value of pixels with average value of similar gray level around the edge points and introduces a kind of adaptive method to determine the high and low threshold value. Applying the improved Canny operators to the robot vision system. The experimental results show that the improved Canny operator can balance the relationship between noise and edge information and extract the edges of the measured object better over the traditional Canny operator.