Document Image Binarization Using Structural Symmetry of Strokes

Abstract

In this paper, a novel local threshold binarization method using structural symmetry of strokes is proposed. Different from most existing local threshold methods which use the whole region to compute the threshold, we estimate the local threshold by only using the structural symmetric pixels (SSP) of the region so as to suppress the non-text pixels and maintain the text ones as well. The SSP is defined as those pixels around strokes whose gradient magnitudes are big enough and directions are opposite. As the gradient map is our basis for computing the SSP, we further propose to estimate background surface first and extract potential SSP in the compensated image so as to deal with degradations of document images such as uneven illumination, low contrast and stain. To prove the effectiveness of our method, tests on two public document image datasets are preformed and the experimental results show that our method outperforms other local threshold binarization approaches on both F-measure and PSNR.