גהאד אלצאנע

אקדמי בכיר

Text Enhancement of Degraded Historical Documents

Reem Alaasam, Boraq Madi, Jihad El-Sana

In this paper, we present an enhancement method for degraded historical handwritten documents. Document enhancement is focused on improving the text quality in document images, and our approach focuses on both denoising and improving the text quality at the same time. We use a generative adversarial network (GAN) model and aim to holistically enhance and denoise the input image and generate a high-quality output image. We tested our model on datasets of different styles and languages and obtained excellent results. In addition, we compare our model with various other approaches and show that our model outperforms them. Throughout different experiments, we show that our model has strong generalization and can be used on datasets of different languages and styles, and can handle degraded historical documents.

שפת פרסום אנגלית
דפים 366-375
סטטוס פרסום פורסם - 01.01.2026

Keywords

Generative Adversarial Networks
Historical Handwritten Documents
Text Enhancement

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science
גישה למסמך
10.1007/978-3-032-09371-4_22
קבצים וקישורים אחרים
Link to publication in Scopus