Image edge detection based on improved ant colony algorithm

Image edge detection is a necessary work in object recognition, feature extraction and structure analysis. Firstly, an improved ant colony algorithm is proposed to solve the problems of partial path selection, low accuracy and low efficiency of traditional ant colony algorithm. The initial pheromone, heuristic function, pheromone update rule and state transition parameters of ant colony algorithm were improved. Finally, the experimental simulation verifies that two classical images are selected to carry out adaptive edge extraction, and the edge detection effect is compared with the traditional detection algorithm. Experimental results show that the improved algorithm can achieve complete and continuous image edge extraction, and verify the effectiveness of the algorithm.