【摘要】 本文设计了一种基于熵的遗传聚类分割算法。该方法以像素的灰度值为特征向量进行编码,利用直方图熵法准则函数作为适应度函数,采用基于排名的选择操作,以一定的概率进行算术交叉和变异,并结合聚类分析设定种群的聚类中心对细胞图像进行遗传聚类分割,获得了较好的分割效果。更多还原

【Abstract】 This paper proposes a genetic clustering image segmentation algorithm based on entropy. Better segmentation effect can be attained by taking the gray levels of pixels as the eigenvector, taking advantage of the histogram entropy principle function as the fitness function, adopting the ranking selection operation, making use of arithmetic crossover and mutation at a certain probability, and combining with the clustering analysis to initialize the clustering center of the population to segment cell images with genetic algorithms.更多还原