计算机科学 ›› 2017, Vol. 44 ›› Issue (1): 100-102.doi: 10.11896/j.issn.1002-137X.2017.01.019
覃晓,梁伟,元昌安,唐涛
QIN Xiao, LIANG Wei, YUAN Chang-an and TANG Tao
摘要： 传统的谱聚类方法使用k-means达到最后的聚类目的。k-means对初始条件敏感,易陷入局部最优,从而导致传统的谱聚类方法应用到图像分割时效果不太理想。将遗传算法用于优化谱方法的聚类阶段,提出一种以遗传算法优化普聚类的图像分割方法(Image Segmentation Algorithm of Spectral Clustering Optimization Based on Genetic,ISCOG)。在合成图像与真实图像上的实验表明ISCOG算法极大地提高了谱聚类算法的稳定性和聚类质量,证明了ISCOG算法的优越性。
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