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MAP-MRF approach for binarization of degraded document image

9 years 4 months ago
MAP-MRF approach for binarization of degraded document image
We propose an algorithm for the binarization of document images degraded by uneven light distribution, based on the Markov Random Field modeling with Maximum A Posteriori probability (MAP-MRF) estimation. While the conventional algorithms use the decision based on the thresholding, the proposed algorithm makes a soft decision based on the probabilistic model. To work with the MAP-MRF framework we formulate an energy function by a likelihood model and a generalized Potts prior model. Then we construct a graph for the energy, and obtain the optimized result by using the well-known graph cut algorithm. Experimental results show that our approach is more robust to various types of images than the previous hard decision approaches.
Jung Gap Kuk, Nam Ik Cho, Kyoung Mu Lee
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICIP
Authors Jung Gap Kuk, Nam Ik Cho, Kyoung Mu Lee
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