A new binarization method for degraded document images

The binarization of image is an important stage in any document analysis system such as OCR. It converts the colored or grayscale images into monochromatic form to reduce the computational complexity in the next stages. In old document images in the presence of degradations (ink bleed, stains, smear, non-uniform illumination, low contrast, etc.) the separation of foreground and background becomes a challenging task. Most of the existing binarization techniques can handle only a subset of these degradations. We present a simple binarization method for old document images. The experimental results confirm that the proposed technique gives good binarization results in the presence of various degradations. It computes the Laplacian of an image to separate the foreground. The subtracted Laplacian image is binarized using a global threshold. Finally, the postprocessing using morphological functions is applied. The results are compared in terms of F-measure, PSNR, time complexity, and OCR based evaluations which shows that our method outperforms existing techniques like Niblack, Sauvola, Gatos, Zhou, NICK, Singh, and Bataineh.