Image segmentation based on the method of the maximal variance and improved genetic algorithm

Aiming for the problem of falling into local optimum when searching for the optimal threshold of the image using normal genetic algorithm, this paper presents a new method based on the maximal variance and improved genetic algorithm to segment the face image. This new method uses the maximal variance of the face gray image as the fitness and changes the problem of image segmentation into a problem of optimization. Adopting genetic algorithm which is characteristic of robustness and adaptability can increase efficiency. As a result, this new method can obtain the optimal segmentation result when applied to different face images. Experiments show that using this method to search for the global threshold can converge the optimal value and decrease the searching time.