Based On Genetic Algorithm For Image Segmentation

Genetic algorithm (GA) has the virtue of simpleness, robustness and parallel in essence. It has been applied perfectly in the engineering field, which appeals to many scholars in the world. In the image segmentation field, GA is usually used to get the threshold of image segmentation.The status of GA applied in the image segmentation field recently is presented, and the theories, steps, results and analyses of several GAs applied in the image segmentation are given.Algorithms and analyses about edge detection and threshold selection of the image segmentation are presented. An overview of the basic theories and the recent development is given, and a new genetic algorithm applied in image segmentation (GAS) is presented.Considering image data is often very massive, GAS introduces three new measures in order to solve the problem of global convergence and improves the convergence speed. Introduction of prepotency operator in the initialize population step and the improved mutation operator accelerate the convergence process, and the introduction of new operator in forming new population step avoid converging in local optimum, and promote the ability of global convergence. Coding based upon image threshold segmentation related with coordinates, using windows crossover method, designing evaluation function based upon the equations given in literature [23], GAS gets much better results than traditional algorithm.Programs were all compiled in the Win98 by VC++6.0. All photos were collected from Internet and personal photos.