Image to Text in 10 Languages: Which OCR Tools Support Your Language?

Why Language Matters for OCR

Not all OCR tools handle all languages equally. A tool that excels at English may struggle with Arabic (right-to-left), Chinese (thousands of characters), or Hindi (complex Devanagari script).

If you need to extract text from images in a non-English language, choosing the right tool matters. Here's what you need to know.

Top 10 Languages for OCR and How They're Handled

1. English

Difficulty for OCR: Easy

Support: Universal — every OCR tool handles English well.

Accuracy: 99%+ on printed text with modern tools.

2. Spanish (Espanol)

Difficulty for OCR: Easy

Notes: Accented characters (a, e, n) are well-supported by all modern tools. No special considerations needed.

Accuracy: 98%+

3. Chinese (Simplified & Traditional)

Difficulty for OCR: Hard

Notes: Over 50,000 unique characters (3,500 commonly used). Traditional OCR struggled with Chinese because character segmentation is more complex. AI OCR handles it much better. Simplified and Traditional are different character sets.

Accuracy: 95-98% with AI tools, 80-90% with traditional OCR.

4. Arabic

Difficulty for OCR: Hard

Notes: Right-to-left (RTL) text. Connected script (letters change shape based on position in a word). Diacritics are often omitted in printed text but important for meaning. Not all OCR tools support Arabic well.

Accuracy: 90-95% with AI tools, 60-75% with traditional OCR.

5. Japanese

Difficulty for OCR: Hard

Notes: Uses three scripts simultaneously: Hiragana, Katakana, and Kanji (Chinese characters). Vertical text is common in traditional print. AI OCR handles this much better than traditional systems.

Accuracy: 95-97% with AI tools.

6. Hindi (Devanagari Script)

Difficulty for OCR: Medium

Notes: Devanagari script has a distinctive horizontal line (Shirorekha) connecting letters at the top. Characters combine in complex ways. Support is growing but not universal among OCR tools.

Accuracy: 90-95% with AI tools.

7. Russian (Cyrillic)

Difficulty for OCR: Easy-Medium

Notes: Cyrillic alphabet has similar letterforms to Latin in some cases (A, K, M, T) but different mappings, which can confuse poorly-designed OCR. Good AI tools handle it easily.

Accuracy: 97%+

8. Korean (Hangul)

Difficulty for OCR: Medium

Notes: Hangul is an alphabetic system where letters are grouped into syllable blocks. The block structure makes it unique. Modern AI OCR handles it well.

Accuracy: 95-97% with AI tools.

9. Turkish

Difficulty for OCR: Easy

Notes: Latin-based alphabet with special characters. Well-supported by most OCR tools.

Accuracy: 97%+

10. Portuguese

Difficulty for OCR: Easy

Notes: Similar to Spanish — accented characters are well-handled. No special considerations for printed text.

Accuracy: 98%+

How ExtractTextFromImage.com Handles Multiple Languages

Our tool uses the GLM-OCR AI model which supports 50+ languages and includes automatic language detection. This means:

• You don't need to select the language manually
• It works on images with multiple languages mixed together
• RTL languages (Arabic, Hebrew) are supported
• CJK languages (Chinese, Japanese, Korean) are supported
• Devanagari, Cyrillic, Thai, and other non-Latin scripts work

Simply upload your image and the AI figures out what language the text is in.

Try it with any language

Tips for Non-English OCR

1. Image quality is even more important for complex scripts like Chinese, Arabic, and Hindi. Use high-resolution images.

2. Font choice matters — standard fonts are recognized better than decorative ones in any language.

3. Handwriting in non-Latin scripts is harder than printed text. Expect lower accuracy.

4. Test your specific tool before committing to a workflow. Not all "50+ language" claims are equally accurate.

Language Support Comparison Table