document: Efficient two-level image thresholding method based on Bayesian formulation and the maximum entropy principle An efficient method for two-level thresholding is proposed based on the Bayes formula and the maximum entropy principle , in which no assumptions of the image histogram are made . An alternative criterion is derived based on maximizing entropy and used for speeding up the searching algorithm . Five forms of conditional probability distributions-simple , linear , parabola concave , parabola convex , and S-function-are employed and compared to each other for optimal threshold determination . The effect of precision on optimal threshold determination is discussed and a trade-off precision epsilon = 0.001 is selected experimentally . Our experiments demonstrate that the proposed method achieves a significant improvement in speed from 26 to 57 times faster than the exhaustive search method
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