Abstract
Because of the different types of document degradation such as uneven illumination, image contrast variation and bleeding-through, binarization for degraded document images is still an enormous challenge for all scholars. This paper presents a new binarization method for degraded document images. The proposed algorithm focuses on the differences of image grayscale contrast in different areas. Firstly, theory of quadtree is used to divide areas adaptively. Secondly, various contrast enhancements are selected to adjust local grayscale contrast for different contrast areas. Lastly, the frequency of gray value is utilized to calculate threshold. The proposed algorithm was tested on the datasets of Document Image Binarization Contest (DIBCO) (DIBCO 2009, H-DIBCO 2010, DIBCO 2011, H-DIBCO 2012). Compared with other five classical algorithms, the binaried images using proposed algorithm gain the highest F-measure and PSNR.
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