An edge detection method based on good point set genetic algorithm

In order to improve the convergence rate of the genetic algorithm based on edge detection, a novel edge detection method based on good point set genetic algorithm(GGA) was proposed. The proposed method first redesigns the crossover operation by using the theory of good point set in which progeny inherits the common genes of parents which represent its family so as to improve the convergence rate of the genetic algorithm. Furthermore, the proposed method offers another better way to improve the convergence rate, that is, to reduce solution domain by pre-processing image to filtering non edge pixel before the algorithm executing. Experimental results show the proposed algorithm performs very well in terms of convergence rate. The detected edge image is well localized, and thin, and robust to noise.