The Image Edge Extraction Algorithm Based on Hough Transform Coupling Ant Colony Optimization

In order to solve the image edge detection algorithm, the edge information is affected by the noise, causing the image edge positioning accuracy is low, Edge information loss and false edges and other issues, proposed a image edge extraction algorithm based on Hough transform (HT)coupling ant colony optimization(ACO).Firstly, introducing the Hough transform to the input image, eliminating the effect of noise and line segment. Secondly, the difference between the pixel gradient of the image and the statistical average of the circular neighborhood is calculated, and the weight function between the two is constructed, and the pheromone and the heuristic information are used as the ant colony. Finally, the ant colony optimization algorithm is used to guide the ant colony to search the edge of the image, so as to finish the image edge extraction. The simulation results show that compared with the current edge detection algorithm, the edge location accuracy and the edge details are abundant, which can effectively restrain the noise, and has better robustness.