Object region extraction based on graph cut and application in image retrieval

Li Guo; Lingjun Wang; Xinghua Sun; Jingyu Yang

doi:10.1117/12.740883

15 November 2007 Object region extraction based on graph cut and application in image retrieval

Li Guo, Lingjun Wang, Xinghua Sun, Jingyu Yang

Author Affiliations +

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67860B (2007) https://doi.org/10.1117/12.740883
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

This paper introduces the technique of graph cut into the extraction of object region and applies the corresponding result of object region extraction into the image retrieval based on object region. The main idea of image retrieval based on object region is to use the feature of object region instead of the feature of global image to participate in the image retrieval. In the field of graphics there is a technique called graph cut, which can be used to figure out the contour of object under the interaction of users. The graph cut algorithm can be used to verify the correctness of object region extraction, and the users' input about seeds can be simulated according to the initial object region extracted. The usage of graph cut can make the object region extracted more precisely and thus the performance of image retrieval based on object region can be improved. Experiments show that the object region extraction algorithm based on graph cut is valid and the subsequent image retrieval results accord with the human visual perception much more than the ones without the usage of graph cut.

Citation Download Citation

Li Guo, Li Guo, Lingjun Wang, Lingjun Wang, Xinghua Sun, Xinghua Sun, Jingyu Yang, Jingyu Yang, "Object region extraction based on graph cut and application in image retrieval", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67860B (15 November 2007); doi: 10.1117/12.740883; https://doi.org/10.1117/12.740883

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