An Improved Visual Theoretic Clustering Algorithm
Shitong Wang · Microcomputer applications · 2006
In order to enhance the cability of the visual theory that applied in the clustering algorithm. An improved visual theoretic clustering algorithm is presented based on the combination of the famous Weber law and the new cost function that is built on the visual theory with the abstract kernel function. Experimental results demonstrate that the improved visual theoretic clustering algorithm not only can realize effective and nonparametric clustering successfully but also can make rational image segmentations.