Is my document safe if I use this OCR tool?

Yes. Our OCR tool runs Tesseract.js entirely within your browser using WebAssembly. No image data is transmitted to any server — you can verify this by opening your browser's Developer Tools (F12) → Network tab and confirming that no upload request occurs after you select an image. The only network requests are the one-time download of Tesseract language model files (which are public, non-personal data). Your images stay on your device. This makes our tool appropriate for sensitive documents like medical records, legal contracts, and financial statements.

What is the difference between OCR and PDF text extraction?

PDF documents come in two types: (1) Text-based PDFs where text is stored as actual digital characters that can be selected, copied, and searched. (2) Image-based PDFs (commonly created by scanning paper documents) where each page is a bitmap image — text exists only as pixels and cannot be selected without OCR. For type 1 PDFs, use our PDF to TXT converter for perfect, instant extraction. For type 2 (scanned) PDFs, convert to image first (screenshot or PDF-to-image tool), then use our OCR tool. The OCR step is only needed when text exists as pixels, not as digital characters.

Why does the first run take longer?

Tesseract OCR requires trained language data — files that teach the engine what English, Chinese, or other language characters look like. These language model files range from 10-25 MB depending on the language. The first time you extract text in a specific language, your browser downloads this file from the Tesseract CDN. Subsequent uses of the same language use the cached file instantly. The download is a one-time cost per browser/device — clearing your browser cache will require a re-download on the next use.

Can OCR read handwriting?

Tesseract can recognize printed block handwriting (clear, separated letters similar to printed text) with moderate accuracy. Cursive handwriting, overlapping letters, or informal handwriting is significantly less accurate with Tesseract because it's primarily trained on printed text. For handwriting recognition, dedicated handwriting OCR services (such as Google Cloud Vision API or Microsoft Azure Computer Vision) use specialized neural network models that significantly outperform Tesseract for handwritten content. Use our tool for printed or typed documents and photographs of signage; use specialized services for handwriting-heavy content.

Utility Tools2026-05-10

OCR Tool — Extract Text from Images Free Online

Optical Character Recognition (OCR) is the technology that reads text from images and converts it into editable, selectable digital text. Before OCR, digitizing a printed document required manually retyping every word. Today, OCR enables instant text extraction from scanned documents, photos of signs, screenshots of non-copyable content, and images of receipts, business cards, or handwritten notes. Our OCR tool runs Tesseract.js directly in your browser — one of the world's most accurate open-source OCR engines, originally developed by HP and maintained by Google. Because Tesseract runs client-side, your images never leave your device: no file is uploaded to a server, no data is stored, and no account is required. This privacy-first approach makes our tool suitable for sensitive documents — medical forms, legal contracts, financial statements — where uploading to a third-party server would be inappropriate.

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OCR Tool

Free · No registration

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Step-by-Step Guide

Select your recognition language

Choose English, Simplified Chinese (简体中文), or Traditional Chinese (繁體中文) based on the primary language of the text in your image. Language selection is critical — OCR accuracy drops significantly when the wrong language model is applied, as different languages have different character shapes and frequency patterns. For mixed-language images (e.g., English technical terms in a Chinese document), select the dominant language and manually correct the minority-language portions afterward.

Upload or drag-and-drop your image

Drag an image file into the upload area or click to browse. Supported formats: JPEG, PNG, and WebP up to 50 MB. For best OCR results, use images with: clear, high-contrast text (dark text on white background); resolution of at least 300 DPI (for scanned documents) or full screen resolution (for screenshots); minimal perspective distortion (image taken straight-on, not at an angle); no severe blur or motion artifacts. Low-quality images will be processed but accuracy decreases substantially with image quality.

Click "Extract Text" and wait for processing

Click the Extract Text button. On the first run, Tesseract downloads the language data for your selected language (approximately 10-20 MB for English, 15-25 MB for Chinese). This one-time download is cached in your browser — subsequent uses of the same language are instant. A progress bar shows recognition progress from 0% to 100%. Processing time depends on image size and complexity: a standard A4 page of text typically takes 3-10 seconds on a modern computer.

Review and edit the extracted text

The extracted text appears in an editable text area. OCR is not perfect — expect occasional errors, especially with: unusual fonts, very small text (below 8pt), handwriting, degraded or aged documents, and images with significant background noise. Review the output for obvious errors. Common OCR mistakes: "0" confused with "O", "1" confused with "l" or "I", "5" confused with "S", accented characters misread. The text area is fully editable — correct errors directly in the output before copying or downloading.

Copy or download the text

Use the Copy button to place the extracted text in your clipboard for immediate pasting into any application. Use the Download .txt button to save the extracted text as a plain text file. For legal or archival purposes, consider downloading the .txt file as a record. The character count displayed below the text area gives you a quick verification of the extraction's completeness — compare it against your manual estimate of how much text the image contained.

Process multi-page documents

Our OCR tool processes one image at a time. For multi-page scanned documents, process each page individually and combine the text files. For PDF documents that contain text as actual text (not scanned images), use our PDF to TXT tool instead — it extracts text with 100% accuracy without OCR processing. Reserve our OCR tool for images and scanned PDFs where the text exists only as pixels, not as embedded digital text.

Tips & Best Practices

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Scan or photograph documents at 300 DPI minimum for best accuracy — photos taken with a modern smartphone camera in good lighting are typically sufficient.

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Use high contrast: place documents on a flat, non-reflective white surface when photographing. Avoid shadows that cross over text.

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Straighten tilted images before processing — OCR accuracy drops noticeably with text tilted more than 5-10 degrees. Use our Image Crop/Rotate tool to correct orientation first.

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For receipts or small-print documents, take a close-up photo or scan at 600 DPI for better accuracy on small text.

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Handwriting recognition: Tesseract can handle printed handwriting (clear block letters) but struggles with cursive or informal handwriting. For handwriting, use a specialized handwriting OCR service.

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After extraction, use Ctrl+A then spell-check in a word processor to quickly identify OCR errors that produce non-words.

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For confidential documents, verify that the tool is running client-side (check your network tab in browser dev tools — no network request should occur during OCR processing) before processing sensitive files.

Frequently Asked Questions

Accuracy depends on image quality. For high-quality images (clear text, good lighting, 300+ DPI, standard fonts), Tesseract achieves 95-99% character accuracy — meaning fewer than 5 errors per 100 characters. For poor-quality images (blurry, low contrast, unusual fonts, small text), accuracy can drop to 70-80%. In practice: a clear scan of a standard document will have very few errors; a photo of text on a coffee-stained receipt in dim lighting will have many. The accuracy metric that matters is whether the extracted text is usable — even 90% accuracy may leave dozens of errors in a 5000-word document that require manual correction.

OCR technology has transformed the way we interact with physical and image-based text, and our browser-based implementation makes professional-quality text extraction available to everyone without accounts, subscriptions, or privacy trade-offs. Upload your image, select the language, extract the text, and copy it directly to your workflow — the whole process takes under a minute for most documents. For high-volume document processing or handwriting recognition, dedicated OCR services offer additional capability; for everyday text extraction from images and screenshots, our tool provides immediate, private, and accurate results.

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