# Degraded Historical Documents Images Binarization Using a Combination of Enhanced Techniques

arXiv: https://arxiv.org/abs/1901.09425 · HTML: https://mlsanity.com/paper/1901.09425/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jan 2019.

## Built on by (most cited first, 1 of 1)

- [Document Image Binarization in JPEG Compressed Domain using Dual Discriminator Generative Adversarial Networks](https://mlsanity.com/paper/2209.05921/) (2022)

## Abstract (arXiv)

Document image binarization is the initial step and a crucial in many document analysis and recognition scheme. In fact, it is still a relevant research subject and a fundamental challenge due to its importance and influence. This paper provides an original multi-phases system that hybridizes various efficient image thresholding methods in order to get the best binarization output. First, to improve contrast in particularly defective images, the application of CLAHE algorithm is suggested and justified. We then use a cooperative technique to segment image into two separated classes. At the end, a special transformation is applied for the purpose of removing scattered noise and of correcting characters forms. Experimentations demonstrate the precision and the robustness of our framework applied on historical degraded documents images within three benchmarks compared to other noted methods.