Multi-Language OCR¶
Definition¶
Identity documents worldwide use 100+ writing systems — Latin, Devanagari, Arabic, Chinese, Cyrillic, Thai, Korean, and more. Multi-language OCR must handle all of these with high accuracy.
Script-Specific Challenges¶
| Script | Challenge | Accuracy |
|---|---|---|
| Latin | Well-solved, many fonts | 98-99% |
| Devanagari | Connected characters, shirorekha (headline), matras | 92-97% |
| Arabic | Right-to-left, connected cursive, contextual forms | 90-96% |
| Chinese | 3,000+ common characters, similar strokes | 95-98% |
| Korean (Hangul) | Syllable blocks, compositional | 96-98% |
| Thai | No word spacing, tonal marks above/below | 92-96% |
| Cyrillic | Similar to Latin but distinct characters | 97-99% |
| Japanese | Three scripts (kanji + hiragana + katakana) mixed | 94-97% |
Multi-Language Solutions¶
| Solution | Approach |
|---|---|
| PaddleOCR | Supports 80+ languages, unified pipeline |
| Tesseract 5 | Open-source, 100+ languages, LSTM-based |
| Google Cloud Vision | Cloud API, broad language support |
| EasyOCR | Python library, 80+ languages |
| TrOCR | Fine-tune per script family |
Key Takeaways¶
Summary
- PaddleOCR is the best practical multi-language solution (80+ languages, fast, mobile-ready)
- Script detection before recognition improves accuracy — route to script-specific model
- Latin and Chinese are well-solved; Arabic and Devanagari remain challenging
- ID documents often have bilingual text — must handle multiple scripts in one image