关键词: 收敛速度, 寻优精度, 柯西分布, 阈值分割

Abstract:

In order to solve the problems of poor anti-noise performance and insufficient segmentation efficiency of the Dtsu method. An adaptive improved step size fruit fly optimization algorithm is proposed, and the Otsu method image segmentation threshold is optimized. According to the fruit fly optimization algorithm which changes the step size according to the change rate of the average value of the concentration, the traditional step size is improved. The early half-Cauchy distribution is an exponential variable, which starts to increase uniformly and then increases in S-shaped adaptively step size. In the later stage, the Cauchy distribution is easy to generate the random number far away from the origin as the operator of the index. The change of the average value of the concentration corresponds to adaptively change the optimal step size of the fruit fly, which is beneficial to jump out of the local optimal solution. Experiments show that the improved algorithm achieves better results in convergence speed and optimization precision, and it is better than other algorithms in the application of image segmentation.

Key words: convergence speed, optimization accuracy, Cauchy distribution, threshold segmentation