一种新的基于佳点集的图像二值化遗传算法

在图像二值化算法中，传统优化算法难达到全局最优解，一般遗传算法不能保证子代的性能优于父代。将佳点集理论应用到图像二值化算法中，建立基于佳点集的随机搜索机制，不仅提高了求解速度与精度，并且能保证所求到的后代的适应值较高。算法具有较好的稳健性，在实际应用中获得了很好的二值化效果，有利于计算机图像处理的后续工作。

A Novel Image Binarization Genetic Algorithm Based on Good Point Set Theory

In the image binarization algorithms,traditional optimization algorithms are difficult to get the best global optimum solution,and normal genetic algorithms cannot promise that the son's performance will be better than the father's.Applies good point set theory to the image binarization algorithm and proposes a random search method based it.These means not only improve the solution's speed and precision,but also ensure that the son's fitness degree will be good.The algorithm has good adaptability,and can achieve excellent effect in the application,and then can do better in the later work of image process.