# Advances and Limitations in Open Source Arabic-Script OCR: A Case Study

arXiv: https://arxiv.org/abs/2402.10943 · HTML: https://mlsanity.com/paper/2402.10943/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 14 references that are in the map.
- First posted on arXiv 8 Feb 2024.

## Builds on (most cited first, 3 of 3)

- [Ground Truth for training OCR engines on historical documents in German Fraktur and Early Modern Latin](https://mlsanity.com/paper/1809.05501/) (2018)
- [BADAM: A Public Dataset for Baseline Detection in Arabic-script Manuscripts](https://mlsanity.com/paper/1907.04041/) (2019)
- [Important New Developments in Arabographic Optical Character Recognition (OCR)](https://mlsanity.com/paper/1703.09550/) (2017)

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

- [Reading or Guessing? Visual Grounding Failures of Vision-Language Models for OCR in Ancient Greek Editions](https://mlsanity.com/paper/2605.27750/) (2026)

## Abstract (arXiv)

This work presents an accuracy study of the open source OCR engine, Kraken, on the leading Arabic scholarly journal, al-Abhath. In contrast with other commercially available OCR engines, Kraken is shown to be capable of producing highly accurate Arabic-script OCR. The study also assesses the relative accuracy of typeface-specific and generalized models on the al-Abhath data and provides a microanalysis of the ``error instances'' and the contextual features that may have contributed to OCR misrecognition. Building on this analysis, the paper argues that Arabic-script OCR can be significantly improved through (1) a more systematic approach to training data production, and (2) the development of key technological components, especially multi-language models and improved line segmentation and layout analysis. Cet article pr'esente une 'etude d'exactitude du moteur ROC open source, Krakan, sur la revue acad'emique arabe de premier rang, al-Abhath. Contrairement `a d'autres moteurs ROC disponibles sur le march'e, Kraken se r'ev`ele etre capable de produire de la ROC extremement exacte de l''ecriture arabe. L''etude 'evalue aussi l'exactitude relative des mod`eles sp'ecifiquement configur'es `a des polices et celle des mod`eles g'en'eralis'es sur les donn'ees d'al-Abhath et fournit une microanalyse des "occurrences d'erreurs", ainsi qu'une microanalyse des 'el'ements contextuels qui pourraient avoir contribu'e `a la m'ereconnaissance ROC. S'appuyant sur cette analyse, cet article fait valoir que la ROC de l''ecriture arabe peut etre consid'erablement am'elior'ee grace `a (1) une approche plus syst'ematique d'entrainement de la production de donn'ees et (2) grace au d'eveloppement de composants technologiques fondamentaux, notammentl'am'elioration des mod`eles multilingues, de la segmentation de ligne et de l'analyse de la mise en page.