# Ancient Script Image Recognition and Processing: A Review

arXiv: https://arxiv.org/abs/2506.19208 · HTML: https://mlsanity.com/paper/2506.19208/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 176 references that are in the map.
- First posted on arXiv 24 Jun 2025.

## Builds on (most cited first, 21 of 21)

- [Restoring ancient text using deep learning: a case study on Greek epigraphy](https://mlsanity.com/paper/1910.06262/) (2019)
- [AGTGAN: Unpaired Image Translation for Photographic Ancient Character Generation](https://mlsanity.com/paper/2303.07012/) (2023)
- [CharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image Denoising](https://mlsanity.com/paper/2207.07798/) (2022)
- [Unsupervised Structure-Texture Separation Network for Oracle Character Recognition](https://mlsanity.com/paper/2205.06549/) (2022)
- [Recognizing Cuneiform Signs Using Graph Based Methods](https://mlsanity.com/paper/1802.05908/) (2018)
- [Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition](https://mlsanity.com/paper/2406.09630/) (2024)
- [HKR For Handwritten Kazakh & Russian Database](https://mlsanity.com/paper/2007.03579/) (2020)
- [RZCR: Zero-shot Character Recognition via Radical-based Reasoning](https://mlsanity.com/paper/2207.05842/) (2022)
- [RCRN: Real-world Character Image Restoration Network via Skeleton Extraction](https://mlsanity.com/paper/2207.07795/) (2022)
- [Chinese Character Recognition with Radical-Structured Stroke Trees](https://mlsanity.com/paper/2211.13518/) (2022)
- [Toward Zero-shot Character Recognition: A Gold Standard Dataset with Radical-level Annotations](https://mlsanity.com/paper/2308.00655/) (2023)
- [Deciphering Undersegmented Ancient Scripts Using Phonetic Prior](https://mlsanity.com/paper/2010.11054/) (2020)
- [Optical Character Recognition of 19th Century Classical Commentaries: the Current State of Affairs](https://mlsanity.com/paper/2110.06817/) (2021)
- [Deep learning classification of large-scale point clouds: A case study on cuneiform tablets](https://mlsanity.com/paper/2202.10851/) (2022)
- [Mixed Model OCR Training on Historical Latin Script for Out-of-the-Box Recognition and Finetuning](https://mlsanity.com/paper/2106.07881/) (2021)
- [CNN based Cuneiform Sign Detection Learned from Annotated 3D Renderings and Mapped Photographs with Illumination Augmentation](https://mlsanity.com/paper/2308.11277/) (2023)
- [STAR: Zero-Shot Chinese Character Recognition with Stroke- and Radical-Level Decompositions](https://mlsanity.com/paper/2210.08490/) (2022)
- [Oracle Character Recognition using Unsupervised Discriminative Consistency Network](https://mlsanity.com/paper/2312.06075/) (2023)
- [Pho(SC)-CTC -- A Hybrid Approach Towards Zero-shot Word Image Recognition](https://mlsanity.com/paper/2105.15093/) (2021)
- [Toward a Period-Specific Optimized Neural Network for OCR Error Correction of Historical Hebrew Texts](https://mlsanity.com/paper/2307.16213/) (2023)
- [VGTS: Visually Guided Text Spotting for Novel Categories in Historical Manuscripts](https://mlsanity.com/paper/2304.00746/) (2023)

## Built on by (most cited first, 6 of 6)

- [Reading or Guessing? Visual Grounding Failures of Vision-Language Models for OCR in Ancient Greek Editions](https://mlsanity.com/paper/2605.27750/) (2026)
- [Interpretable Oracle Bone Script Decipherment through Radical and Pictographic Analysis with LVLMs](https://mlsanity.com/paper/2508.10113/) (2025)
- [EpiSAM: Character Segmentation in Challenging Stone Inscriptions](https://mlsanity.com/paper/2606.28859/) (2026)
- [Towards Computational Chinese Paleography](https://mlsanity.com/paper/2601.06753/) (2026)
- [Scribe Verification in Chinese manuscripts using Siamese, Triplet, and Vision Transformer Neural Networks](https://mlsanity.com/paper/2603.13877/) (2026)
- [Zero-Shot SAM2 Segmentation and Vision Transformer-Based Recognition of Elamite Cuneiform Symbols from Degraded Tablet Images](https://mlsanity.com/paper/2608.18544/) (2026)

## Abstract (arXiv)

Ancient scripts, e.g., Egyptian hieroglyphs, Oracle Bone Inscriptions, and Ancient Greek inscriptions, serve as vital carriers of human civilization, embedding invaluable historical and cultural information. Automating ancient script image recognition has gained importance, enabling large-scale interpretation and advancing research in archaeology and digital humanities. With the rise of deep learning, this field has progressed rapidly, with numerous script-specific datasets and models proposed. While these scripts vary widely, spanning phonographic systems with limited glyphs to logographic systems with thousands of complex symbols, they share common challenges and methodological overlaps. Moreover, ancient scripts face unique challenges, including imbalanced data distribution and image degradation, which have driven the development of various dedicated methods. This survey provides a comprehensive review of ancient script image recognition methods. We begin by categorizing existing studies based on script types and analyzing respective recognition methods, highlighting both their differences and shared strategies. We then focus on challenges unique to ancient scripts, systematically examining their impact and reviewing recent solutions, including few-shot learning and noise-robust techniques. Finally, we summarize current limitations and outline promising future directions. Our goal is to offer a structured, forward-looking perspective to support ongoing advancements in the recognition, interpretation, and decipherment of ancient scripts.