Computer Science ›› 2016, Vol. 43 ›› Issue (11): 309-312.doi: 10.11896/j.issn.1002-137X.2016.11.060

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Image Co-segmentation by Constraints of Shape

PAN Xiang, YU Hui-bin, ZHENG He-rong and LIU Zhi   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Existing image co-segmentation method fails to consider the similarity of shape between images,so that the segmentation results are inconsistent.We introduced a method of interactive image co-segmentation by the constraints of shape.First,the method preprocess an input image and finds the template of shape.Secondly,shape context matching algorithm is used to produce foreground and background mask for graph cut.Finally,minimum cut theory is used to optimize segmentation boundary.The experimental results show that compared with existing image co-segmentation method,this algorithm can significantly improve the quality of segmentation and make the segmentation results more semantical.

Key words: Image co-segmentation,Shape template,Shape context,Graph cut

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