OCR Online Free — Extract Text from Images
The free OCR tool uses optical character recognition to extract text from any image — scanned documents, photos of signs, screenshots, and more. It supports 15+ languages and runs entirely in your browser using Tesseract.js, so no image is ever uploaded to a server.
What Is OCR and How Does It Work?
Optical Character Recognition (OCR) is the process of identifying text within an image and converting it into editable, searchable characters. When you scan a printed page or photograph a document, the result is a raster image — a grid of pixels. OCR software analyses that pixel grid, detects shapes that correspond to letters and numbers, and outputs the recognized text.
This tool uses Tesseract.js, a WebAssembly port of the Tesseract OCR engine originally developed at HP and now maintained by Google. Tesseract is one of the most accurate open-source OCR engines available and supports over 100 languages in its full version, with 15+ of the most common languages available in this browser-based implementation.
How to Extract Text from an Image
- Open the OCR — Image to Text tool.
- Click Choose File or drag an image onto the upload zone. Supported formats: PNG, JPG, GIF, BMP, TIFF, WebP.
- Select the language of the text in the image from the language dropdown.
- Click Recognise Text.
- The extracted text appears in the output panel. Click Copy to copy it to your clipboard.
Recognition time depends on image size and complexity. A simple typed page typically takes 3–10 seconds. Dense multi-column layouts or handwriting may take longer.
Supported Languages
| Language | Script | Notes |
|---|---|---|
| English | Latin | Best accuracy; most training data available |
| Arabic | Arabic (RTL) | Right-to-left text; clear print performs best |
| Chinese (Simplified) | Han | Printed text; handwriting not supported |
| French, German, Spanish, Italian | Latin | High accuracy on typed text |
| Hindi | Devanagari | Good on clear, printed text |
| Japanese, Korean | Mixed / Hangul | Printed text; vertical layouts may vary |
| Russian, Ukrainian | Cyrillic | High accuracy on standard printed documents |
Tips for Better OCR Accuracy
Use high-resolution images
OCR accuracy improves significantly with higher resolution. Aim for at least 300 DPI for scanned documents. If photographing text with a phone, ensure the image is in focus and well-lit. Blurry or low-light photos are the most common cause of poor results.
Straighten the image before processing
Tesseract handles moderate skew (pages photographed at a slight angle), but results are better on straight, flat scans. If your image is significantly rotated, use your phone's crop and straighten tool before uploading.
Choose the correct language
Selecting the wrong language is a common mistake. If a document is in French but you leave the language set to English, the OCR engine will misrecognise accented characters like é, à, and ç. Always match the language setting to the language of the text in the image.
Typed text outperforms handwriting
Tesseract is optimised for printed and typed text. Handwritten text recognition is much less accurate — expect partial results at best. If you need to digitise handwritten notes, consider typing them manually or using a dedicated handwriting recognition app.
Common OCR Use Cases
- Extracting text from scanned contracts or legal documents
- Copying text from a screenshot or PDF image
- Digitising printed receipts for expense tracking
- Extracting data from photographed forms or invoices
- Making scanned PDFs searchable by extracting and copying their text
OCR and Scanned PDFs
If you have a scanned PDF — a PDF where the pages are images rather than selectable text — you can take a screenshot or export a page as an image and run it through the OCR tool. Once you have the extracted text, you can paste it into a Word document or use the PDF ↔ Word Converter to work with the content further.
Privacy: Your Images Never Leave Your Device
Tesseract.js runs entirely in your browser as a WebAssembly module. Your image is processed in local memory — no pixel data is sent to any server. This makes the tool appropriate for confidential documents, ID scans, or any sensitive material.
Extract Text from Images Free
15+ languages, no uploads, no account. Optical character recognition in your browser.
Open OCR — Image to Text