Fast mean shift segmentation based on correlation comparison algorithm
Yanling Li, Gang Li · 2012
Mean-shift is an effective statistical iterative algorithm. In the iterative process, size of bandwidth has great impact on the accuracy and efficiency of the algorithm. It not only decides the number of sampling points in the iteration, but also affects the convergence speed and accuracy of the algorithm. So, the choice of bandwidth is very important. In this paper, bandwidth is calculated by using correlation comparison algorithm, and then mean shift algorithm is used for image segmentation. Experimental results show that better image segmentation result can be obtained by using this new algorithm.