An Image Co-Segmentation Algorithm Using Hyper-Graphcut
Yuan Fe · Xi'an Jiaotong Daxue xuebao · 2014
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 cosegmentation 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%.