Academy & Industry Research Collaboration Center (AIRCC)

Volume 9, Number 7, June 2019

Solving the Binarization Challenges in Document Images Using OTSU Multilevel


Enas M. Elgbbas, Mahmoud I. Khalil, Hazem Abbas, Ain Shams University, Egypt


This paper introduces a method for binarization of historical document images that suffer from non-uniform background, faint text, low contrast, stain, bleed-through, or shadow challenges. The proposed method adaptively detects the non-uniform background in the document image and eliminates it. Areas that contain missing text are adaptively identified and reprocessed separately. Stain and bleed-through objects are found depending on stroke width and locally binarized. Shadow is detected based on the image contrast. Otsu multilevel is applied for binarization. DIBCO series is used for testing.


Document image binarization, Otsu multilevel