The two-dimensional double-entropy threshold based on the parallel genetic simulated annealing algorithms

In this paper, aiming at solving the problem arising from the application of the two-dimensional entropy method in double threshold segmentation, which is time-consuming and highly complex, the author introduces the parallel genetic simulated annealing algorithm to optimize it. Besides, the author structures parallel genetic simulated annealing algorithm to search for a two-dimensional maximum entropy value of the optimal threshold. This optimized algorithm shortens the calculation time, accelerates the speed of obtaining the optimal threshold and improves the efficiency of image segmentation.