Binarization of a gray scale document image is one of the most important steps for automatic document processing. This paper presents a two-stage document image binarization approach. The approach applies a region-based binarization technique first to the whole image and utilizes a neural network based binarization technique to those text blocks in which a good character segmentation cannot be achieved at the first stage. Experimental results on a number of document images show that our two-stage binarization approach performs better than other binarization techniques in terms of character segmentation quality and computing time.
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