Image Edge Detection Based on the Canny Edge and the Ant Colony Optimization Algorithm

In order to solve the problem of edge discontinuity in traditional edge detection methods, a new edge detection method is proposed, which combines the Canny operator and improved the ant colony optimization algorithm. In this method, firstly, the edge of the image is extracted by the traditional Canny operator. Then the endpoint of the edge is calculated as the initial position of the ant. The fuzzy triangle membership function is introduced by the gray value in the neighborhood. The fuzzy membership value of each pixel between the edge endpoints is calculated as the heuristic matrix of the ant colony. The heuristic matrix promotes ants to search along the real edge to detect continuous and complete edge lines. The experimental results show that the proposed method effectively improves the accuracy of contour extraction of target objects in images, and the edge information extracted by this method is clearer.