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In this paper we present a combined binarization technique for historical document images. Usually, many binarization techniques are implemented in the literature for different types of binarization problems. The few simple available thresholding methods cannot be applied to many binarization problems. In order to improve the quality of historical document images, we propose a combined approach based on global and local thresholding methods. The method was evaluated on the benchmarking dataset used in the Handwritten Document Image Binarization Contest (H-DIBCO 2012) and an Arabic historical document from National Library of Algeria. The evaluation based on the word spotting system showed the efficiently of our approach.

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