Semi-supervised Segmentation Based on Level Set

Abstract

The segmentation result of Region-based Active Contour (RAC) usually has little relationship with the initial contour which brings difficulties for Human-Computer Interaction. Based on the interactive information between user and system as the prior knowledge, this paper proposed an interactive object segmentation algorithm RIS. The model proposed is based on the active contour without edge (CV) and the prior shape. As the reason of imprecise prior shape user inputs, the weighted area algorithm based on the gradient and laplace was introduced. To overcome the issue of shrink of the object contour, a new area inspiring item was added into the energy function. The experimental results have shown that, without the prior knowledge model based on the shape training set, the proposed algorithm can segment ROI based on the user inputs information.