An image co-segmentation algorithm using hyper-graphcut

作者：Yuan Fei; Zhu Li; Zhang Lei

来源：Journal of Xi'an Jiaotong University, 2014, 48(2): 20-24+37.

DOI：10.7652/xjtuxb201402004

• Graph-cut
• Hyper-graph
• Image co-segmentation
• Spectral analysis

An image co-segmentation algorithm using hyper-graphcut is proposed to improve the efficiency of image co-segmentation algorithms based on traditional graph-cut for the high computational complexity in optimizing energy functions. The algorithm bases on the property that hyper-graphs represent the relationship among images better. Mean-shift over-segmentation is applied to the input image pair to obtain image patches and these patches are then expressed as the nodes of a hyper-graph. Then the similarities between patches are calculated through their color histogram features, and the collections of similar patches and their neighbor patches are set as hyper-edges and a hyper-graph is constructed. The spectral analysis algorithm is performed on the constructed hyper-graph to obtain the final co-segmentation result of the image pair. Experimental results and comparisons with the normalized-cut of single image and the co-segmentation algorithm based on graph-cut show that the proposed algorithm has a notable improvement on image co-segmentation efficiency with a calculation cost reduction at least 45.

• 出版日期2014
• 单位北京理工大学