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Comparison of Five Conditional Probabilities in 2-Level Image Threshold Based on Bayesian Formulation
Chang, Y., Fu, A.M.N., Yan, H. and Zhao, M.
In this paper, 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. 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 experiment results show that the Parabola Concave form is the most effective, retaining most of the information for most thresholding images. The Linear form is an acceptable form due to its simple first-order linear function |
Cite as: Chang, Y., Fu, A.M.N., Yan, H. and Zhao, M. (2001). Comparison of Five Conditional Probabilities in 2-Level Image Threshold Based on Bayesian Formulation. In Proc. Selected papers from Pan-Sydney Area Workshop on Visual Information Processing (VIP2000), Sydney, Australia. CRPIT, 2. Eades, P. and Jin, J., Eds. ACS. 79-81. |
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