Scanned PDF OCR in 125 Languages

In the modern digital era, information is everything. But too often, valuable knowledge is locked away inside scanned documents—unsearchable, uneditable, and difficult to use. If you’ve ever received a PDF file that was just an image of text, you’ve experienced this frustration firsthand. You can’t copy and paste the text, you can’t search for specific keywords, and making edits seems impossible without retyping the entire document.

This is where OCR (Optical Character Recognition) technology comes in. OCR transforms scanned PDFs into machine-readable, searchable, and editable text. It bridges the gap between static images of documents and the dynamic world of digital data processing.

Optical Character Recognition (OCR) is the process of analyzing images of text (like scanned documents or photos) and converting them into machine-encoded text. In other words, OCR turns pictures of words into actual text data.

With our modern OCR tool supporting up to 125 languages, organizations and individuals can transform massive archives of scanned files into fully searchable, multilingual, and accessible resources. Our OCR engine can recognize and correctly interpret text across a wide spectrum of:

Major world languages (English, Spanish, Arabic, Hindi, Chinese).
Regional languages (Swahili, Basque, Catalan).
Scripts (Latin, Cyrillic, Greek, Devanagari, Arabic, Hanzi, Hangul, etc.).

Below is a consolidated alphabetical list for quick reference:

Afrikaans, Albanian, Amharic, Ancient Greek, Arabic, Armenian, Assamese, Azerbaijani, Basque, Belarusian, Bengali (Bangla), Bosnian, Breton, Bulgarian, Canadian Aboriginal Alphabet (Canadian First Nations), Catalan, Cebuano (Bisaya), Cherokee, Chinese Simplified, Corsican, Croatian, Cyrillic (Cyrillic scripts), Czech, Danish, Devanagari, Divehi, Dutch (Nederlands), Dzongkha, Esperanto, Estonian, Ethiopic Alphabet (Ge'ez), Faroese, Filipino, Financial Language Pack (spreadsheets & numbers), Finnish, Fraktur (Generic Fraktur), Frankish, French, Galician, Georgian, German, Greek, Gujarati, Gurmukhi Alphabet, Haitian (Kreyòl ayisyen), Han Simplified Alphabet (Samhan), Hangul (Hangul alphabet), Hebrew, Hindi, Hungarian, Icelandic, Indonesian (Bahasa Indonesia), Inuktitut, Irish (Gaeilge), Italian, Japanese (including vertical variants), Javanese, Kannada, Kazakh, Khmer, Korean, Kyrgyz, Lao, Latin, Latin Alphabet, Latvian, Lithuanian, Luxembourgish, Macedonian, Malay (bahasa Melayu), Malayalam, Maltese, Maori (te reo Māori), Marathi, MICR (Magnetic Ink Character Recognition), Middle English (English 1100–1500 AD), Middle French (Moyen Français), Mongolian, Myanmar (Burmese), Nepali, Northern Kurdish (Kurmanji), Norwegian, Occitan, Oriya (Odia), Panjabi (Punjabi), Pashto, Persian (Farsi), Polish, Portuguese, Quechua (Runa Simi), Romanian, Russian, Sanskrit, Scottish Gaelic (Gàidhlig), Serbian, Sindhi, Sinhala, Slovak, Slovenian, Somali, Spanish, Sundanese, Swahili, Swedish, Syriac, Tagalog, Tajik, Tamil, Tatar, Telugu, Thaana Alphabet, Thai, Tibetan, Tigrinya, Tonga (faka Tonga), Turkish, Ukrainian, Urdu, Uyghur, Uzbek, Vietnamese, Welsh, Western Frisian, Yiddish, Yoruba

When choosing a language, you can select from different quality options — Fast, Standard, and Best — which offer a trade-off between processing speed and accuracy. You can also use second language at once for documents containing more than one language.

The accuracy of OCR is only as good as the quality of the images being processed. This is where OCR combined with image enhancement steps in. Image enhancement refers to digital processing techniques that improve image quality for better human readability and machine interpretation. It improves OCR accuracy by:

Automatic Deskew: Straightens tilted scans so text lines are horizontal.
Sharpen: Sharpening helps refine letter edges, making characters more distinguishable.
Binarization: Converting grayscale/color images into black-and-white improves contrast. Techniques like Otsu’s thresholding or adaptive thresholding make text clearer.

The extracted text can be export into multiple output formats: azw3, doc, docm, docx, dot, dotm, dotx, epub, flatopc, html, md, mht, mobi, odt, ott, pdf, rtf, txt, xlsx, xps