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模糊Ｃ－均值算法是一种比较有效的数据聚类方法．遗传算法则是一种借鉴生物界自然选择和自然遗传机制的高度并行、随机、自适应的搜索算法．该文有机地利用遗传算法与模糊Ｃ－均值算法，并考虑图象的二维灰度信息，提出了一种适用于多阈值图象自动分割的新方案．该方案能够快速正确地实现分割，且不需事先认定分割类数．实验结果令人满意
Fuzzy C-means algorithm is a more effective method of data clustering. Genetic algorithm is a highly parallel, random and adaptive search algorithm that draws on the natural selection and natural genetic mechanism in the biological world. This paper presents a new scheme which is suitable for automatic segmentation of multi-threshold images by using genetic algorithm and fuzzy C-means algorithm. Considering the two-dimensional gray information of images, The program can quickly and correctly achieve segmentation, and without prior recognition of the number of segmentation class. The experimental results are satisfactory