A Study For The Color Image Segmentation Based On Genetic Algorithm

Genetic algorithm (GA) is a randomized parallel search algorithm that model natural selection, the process of evolution. GA has been widely used in engineering problems. When the genetic algorithm is implemented it is usually done in a manner that involves the following cycle: Evaluate the fitness of all of the individuals in the population. Create a new population by performing operations such as selection, crossover and mutation on the individuals whose fitness has just been measured . Discard the old population and iterate using the new population.In this thesis, the theories and methods of GA are analyzed in detail , the trend of GA in recent times is briefly discussed. Because of the importance of image segmentation, two methods of color image segmentation based on GA are proposed. One is the surface of thresholds image segment method, the other is entropic threshold method. Two algorithms are realized through VC++ 6.0. After that, we compare the characteristics of two algorithms and prove that GA can be very well applied to solving image optimal problems.