Image Edge Detection Algorithm Based on The Parallel Genetic and Otsu dual-threshold

Abstract

Abstract. The traditional genetic algorithm is used to search some function extreme value, but it has low precision and poor stability. For this shortage, A kind of parallel genetic algorithm based on Otsu double threshold algorithm of image edge detection, the design into a line of two columns of the vector population, than as an individual's fitness variance between, generated a number of initial population of parallel computing, At the same time, the largest fitness individuals in each generation directly copied into the next generation, evolution in a number of different subgroup in parallel, in order to avoid the premature convergence phenomenon appeared in the process of single population evolution, to improve the algorithm convergence speed. The experimental results show that the algorithm is compared with the traditional genetic algorithm, can more accurate and has better accuracy and stability.