Evaluating Cloud and Self-Hosted OCR Systems for Arabic, English, and French Documents: Bounding Box Detection, Text Recognition, and Mathematical Expression Recognition
Choosing an OCR system for a multilingual archive requires balancing accuracy against deployment constraints. This study compares cloud and self-hosted systems on three tasks: bounding box detection on 48 Arabic, English, and French pages, text recognition on 315 pages across nine document types, and mathematical expression recognition on 83 English and Arabic samples. Detection was assessed by page-level visual grades, text by character error rate (CER) against a Gemini-generated reference transcription, and mathematics by scores against known answers. Main estimates are accompanied by 95% intervals and paired comparisons. Google Document AI and Surya produced Good line boxes on 47 of 48...
| Authors | Jumana Alsubhi, Ahmed Alhusayni, Abdulrahman Gharawi et al. |
|---|---|
| Primary category | cs.CV |
| Published | 18 October 2026 |
| Last updated at source | 18 October 2026 |
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