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• W2007083035 abstract "The multi-level image thresholding is often treated as a problem of optimization. Typically, finding the parameters of these problems leads to a nonlinear optimization problem, for which obtaining the solution is computationally expensive and time-consuming. In this paper a new multi-level image thresholding technique using synergetic differential evolution (SDE), an advanced version of differential evolution (DE), is proposed. SDE is a fusion of three algorithmic concepts proposed in modified versions of DE. It utilizes two criteria (1) entropy and (2) approximation of normalized histogram of an image by a mixture of Gaussian distribution to find the optimal thresholds. The experimental results show that SDE can make optimal thresholding applicable in case of multi-level thresholding and the performance is better than some other multi-level thresholding methods." @default.
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• W2007083035 date "2014-04-01" @default.
• W2007083035 modified "2023-09-23" @default.
• W2007083035 title "Multi-level image thresholding by synergetic differential evolution" @default.
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• W2007083035 doi "https://doi.org/10.1016/j.asoc.2013.11.018" @default.
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