Document image binarization is one important processing step, especially for data analysis. In this paper, a new binarization based local thresholding technique 'WAN' was presented. The proposed algorithm is known as 'WAN' after the first name of the author in this paper. WAN has been inspired from the Sauvola's binarization method and exhibits its robustness and effectiveness when evaluated on low quality document images. The objective of the WAN method is to improve the Sauvola method and achieve a better binarization results, specifically, for non-uniform document images. The results of the numerical simulation indicate that the WAN method is the most effective and efficient (f-measure 72.274 and NRM = 0.093) compared to the Sauvola method, Local Adaptive method, Niblack method, Feng Method, and Bernsen method.
