An improved GrabCut using a saliency map
Kwang-Shik Kim, Yeo-Jin Yoon, Mun-Cheon Kang, Jee-Young Sun, Sung-Jea Ko · 2014
The GrabCut, which uses the graph-cut iteratively, is popularly used as an interactive image segmentation method since it can produce the globally optimal result. However, since the initialization of the GrabCut is roughly performed by the manual interaction, the accuracy of the segmentation result is not guaranteed when the user defines an inaccurate guide. To solve this problem, in this paper, we present an improved GrabCut method which uses a visual saliency of the target region for the effective initialization. Experimental results demonstrate that the proposed method provides more accurate segmentation results compared with the conventional method.