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- W2361904812 abstract "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%." @default.
- W2361904812 created "2016-06-24" @default.
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- W2361904812 date "2014-01-01" @default.
- W2361904812 modified "2023-09-23" @default.
- W2361904812 title "An Image Co-Segmentation Algorithm Using Hyper-Graphcut" @default.
- W2361904812 hasPublicationYear "2014" @default.
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