Semi-supervised image segmentation with globalized probability of boundary and simple linear iterative clustering
Junliang Ma, Wang Xili, Bing Xiao · 2017
Semi-supervised image segmentation in order to get a divided image from the tag portion. In this paper, a new semi-supervised image segmentation framework with global boundaries of probability (gPb) and simple linear iterative clustering (SLIC) is proposed. We use SLIC to perform image segmentation of super pixels, and we have constructed a graph, in which each vertex is a superpixel. Then we utilize gPb to define the edge weights for the graph. Semi-supervised learning based image (GSSL) method, and the use of labeled samples to calculate anchor anchor category, the category may be further determined by the anchor point of the sample. The results of the experiments certify the robustness and effectiveness of the method proposed in this paper.