Batch Image to Text (OCR) in 125 Languages

In today’s digital era, images are everywhere. From scanned documents, handwritten notes, old books, and invoices to social media graphics, images often contain critical textual information. However, text locked inside images is not searchable, editable, or easily translatable without the right tools. This is where OCR (Optical Character Recognition) comes in.

OCR, or Optical Character Recognition, is a process that converts text embedded in images into editable and searchable text. Batch OCR is the process of performing OCR on multiple images at once. Instead of manually converting text from individual files, batch OCR automates the workflow, making it possible to process thousands of images, scanned pages, or documents in minutes.

The internet and business are global. Documents aren’t limited to English—they can be in Spanish, Chinese, Arabic, Hindi, Vietnamese, or Swahili. Our OCR software supports 125 languages across diverse scripts, including:

Latin scripts: English, Spanish, French, German, Italian, Portuguese
Asian scripts: Chinese (Simplified/Traditional), Japanese, Korean, Thai, Vietnamese
Indic scripts: Hindi, Bengali, Tamil, Gujarati, Punjabi, Marathi
Middle Eastern scripts: Arabic, Persian, Hebrew, Urdu
Slavic languages: Russian, Polish, Czech, Serbian, Bulgarian
African languages: Swahili, Amharic, Afrikaans

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.

Our OCR tool handles multiple image formats, including: avif, bmp, dib, emf, exr, gif, heic, heif, j2k, jfif, jp2, jpe, jpeg, jpg, png, psb, psd, svg, tga, tif, tiff, webp, wmf

The accuracy of OCR is only as good as the quality of the images being processed. This is where image enhancement comes into play—especially in batch OCR scenarios, where thousands of images must be processed simultaneously and efficiently. Image enhancement involves a suite of preprocessing techniques, including:

Automatic Deskew: Scanned pages are often tilted. Deskewing algorithms straighten images, ensuring that lines of text are properly aligned for OCR engines.
Sharpen: Enhancing edges improves clarity, making blurred text easier to recognize.
Binarization: Converting images into black and white simplifies text recognition. Methods like Otsu’s thresholding ensure that text stands out against the background.

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

The tool also allows users to merge extracted text into unified, organized document (optional). Instead of dealing with dozens or even hundreds of separate text files, merging allows you to combine OCR results into cohesive documents.