Automated seeded region growing method for document image binarization based on topographic features

Binarization of document images with poor contrast, high noise and variable modalities remains a challenging problem. This paper proposes a new binarization method that adopts the use of seeded region growing and character's topographic feature. It consists of three steps: first, seed pixels are selected automatically according to their topographic features; second, regions are grown controlled by new weighted priority until all pixels are labeled black or white; third, noisy regions are removed based on the average stroke width feature. Our method overcomes the difficulty of global binarization to find a single value to fit all. It also avoids the common problem in most local thresholding technique of finding a suitable window size. The proposed method performed well in binarization and the experimental results of evaluation showed significant improvement compared to several other methods.