A new image co-segmentation method using saliency detection for surveillance image of coal miners |
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| Affiliation: | 1. College of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China;2. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China;3. School of Physics and Engineering, Qufu Normal University, Qufu, Shandong 273165, China;1. Department of Electrical Engineering, COMSATS Institute of Information Technology, Park Road, Chak Shahzad, 44000 Islamabad, Pakistan;2. Center for Advanced Studies in Telecommunications, COMSATS Institute of Information Technology, Park Road, Chak Shahzad, 44000 Islamabad, Pakistan;3. Department of Physics, COMSATS Institute of Information Technology, Park Road, Chak Shahzad, 44000 Islamabad, Pakistan;1. V. Lashkaryov Institute of Semiconductor Physics of NASU, pr. Nauky 41, 03028 Kyiv, Ukraine;2. The Institute of Molecular Biology and Genetics of NASU, Zabolotnogo Str. 150, 03680 Kyiv, Ukraine;3. Instituto Politécnico Nacional – ESIME, Av. IPN, Ed. Z4, U.P.A.L.M., 07738 Mexico D.F., Mexico |
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| Abstract: | ![]()
In this paper, we propose a co-segmentation method using saliency detection. The input image is first over-segmented into super-pixels, in which, their similarities are measured by the Bhattacharyya coefficients. The proposed method uses the combination of detection results of different detection methods on different types of color space to produce the originating regions, in which optimized linear coefficient combination is exploited. Experiments are performed on different image databases and results comparable to that of some current state-of-the-art methods are provided. |
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