基于K-均值与蚁群混合聚类的图像分割

针对单一聚类算法在图像分割中容易陷人局部最优或有过分割现象,造成分割精确度低等问题,文章提出了基于K-均值聚类和蚁群聚类相结合的新算法.新算法先将K-均值算法作快速分类,根据K-均值分类结果更新蚂蚁各路径上的信息素,指导其他蚂蚁选择,以提高蚁群聚类算法的运行效率.实验结果证明,新算法在图像分割处理的精确度上较单一的K均...

Image Segmentation Method Based on Combining Ant Colony Clustering with K-means Algorithm

For a single clustering algorithm for image segmentation is easy to fall into local optimum or the phenomenon of over-segmentation,which will result in low accuracy problem of segmentation,We put forward a new clustering algorithm combining ant colony clustering with K-means algorithm.The new clustering algorithm is the first K-means algorithm for rapid classification,and according to classification results update the pheromones to guide the choosen of other ants,to improve the efficiency of ant colony clustering algorithm.Experimental results show that the new algorithm for image segmentation accuracy than a single K means clustering algorithm and the ant colony clustering algorithm has greatly improved.Therefore,further show that this method for image segmentation has good versatility and effectiveness,is a practical and promising method of image segmentation.