Interactive Image Segmentation Based on Multi-level Cooperative Propagation
Shen Qun-tai · Jisuanji gongcheng · 2013
Existing interactive segmentation algorithms are sensitive to quantity as well as placement of user’s scribbles,hence a novel algorithm which employs region cue is proposed.Segmentation result by mean-shift algorithm is regarded as imaginary pixels,and further incorporated into construction of two-layer weighted graph,which provides long range connection between homogenous semantic areas.Then all these connections are integrated in a chrominance iteration formulation,which performs updating to membership of all pixels to every label.Segmentation is completed via comparison to resulting membership.Experimental results indicate that even little amount of scribble can result in satisfactory result,which demonstrates that the proposed method has higher robustness to quantity and placement of scribbles in comparison with existing mono-layer ones.