An application of stochastic heuristic search method to edge extraction in noisy images

How to extract the edge effectively in noisy image is a difficult problem of pattern recognition. In this paper, we present a stochastic heuristic search algorithm to extract edge in noisy image. We use repetitive random searches to obtain various possible independent-edge trajectories in the edge image, then self-reinforce and accumulate the search trajectories respectively, at last, extract the edges based on the results of the accumulation of self-reinforcement. Our technique combines the local information of the edge points and the whole information of independent-edge curves availably. Lots of experiments and comparing with past heuristic search algorithms, we find that our method can extract edges effectively and suppress the noise.