Application of Simulated Annealing Algorithm in Pest Image Segmentation

Traditional pest detection methods can´t provide the grain pests´ categories, densities and other parameters. In addition, with the increase of the stored-grain pests´ drug fastness, their categories and densities are increasing in recent years, With the development of pattern recognition, image processing, intelligent algorithm, computer technology, develop a new detection system is necessary and imperious. Image segmentation is a key step in this system. In this paper, the basis of image segmentation is introduced; the improved fuzzy C-means clustering based on simulated annealing algorithm is applied to the stored-grain image segmentation. The Matlab simulation experiments demonstrate that this method is more effective than fuzzy C-means clustering and classic segmentation algorithm, and it can segment the pest image better.