Image to Text OCR
Extract editable text from images with private browser-based OCR, language support, live progress, and instant copy or TXT download.
OCR Settings
Image Preview
Related Tools
About the Image to Text OCR
Optical Character Recognition (OCR) converts pictures of text into actual text: a photographed receipt becomes searchable numbers, a scanned page becomes quotable paragraphs, a screenshot of an error message becomes copyable code. Once extracted, text can be edited, translated, searched, and stored — things pixels can never do.
This tool runs real OCR entirely inside your browser using WebAssembly — the recognition engine loads to your device, and recognition happens there. Photograph documents, screenshots, book pages, or whiteboards; preview the image, run recognition, and get editable text with a confidence-aware readout. Nothing uploads: sensitive documents (IDs, medical reports, contracts) stay yours.
Accuracy has physics on its side: sharp focus, even lighting, and straight alignment dramatically improve results. The tips below cover the small habits that turn 70% accuracy into 98%.
How to use the Image to Text OCR
- 1 Add a photo, scan, or screenshot containing text.
- 2 Review the preview — crop tightly around the text region if possible.
- 3 Run OCR; the engine processes locally and extracted text appears.
- 4 Copy or download the text; clean up minor spacing issues if the source was photographed at an angle.
Key features
Browser-native OCR engine
WebAssembly recognition with no upload, no account, no limits.
Multi-language support
Recognises English and major world scripts including Devanagari.
Preview-and-crop
Limit recognition to the region that matters for speed and accuracy.
Copy or .txt download
Extracted text flows straight into notes, docs, or spreadsheets.
Who uses the Image to Text OCR?
- Digitising printed notes, book pages, and library material for study.
- Extracting text from screenshots: error messages, code, chat threads.
- Converting receipts and invoices into editable expense records.
- Making printed forms searchable before archiving.
- Accessibility: turning textbook images into screen-reader text.
- Journalists and researchers quoting printed sources accurately.
Tips and best practices
- Lighting beats software: even, shadow-free light with no glare outperforms any correction pass.
- Fill the frame with text — camera 15–25 cm from the page beats a distant wide shot.
- Keep pages flat and the camera parallel; keystone distortion from angles degrades accuracy measurably.
- For screenshots, prefer PNG (lossless) over JPG; compression artefacts confuse character edges.
- Tables and columns extract best row-by-row: crop and recognise one column at a time for clean structure.
- Handwriting varies: cursive remains unreliable, but neat block-letter notes often recognise well.
Frequently asked questions
No. The recognition engine runs locally in your browser via WebAssembly — images never leave your device.
English out of the box with support for major scripts including Devanagari; recognition quality is best on printed text with clean typography.
Usually optics: blur, glare, shadows, or skew. Re-shoot closer with even light and the camera parallel to the page before blaming the engine.
Neat block letters often work; cursive and stylised handwriting remain unreliable. OCR is strongest on printed and typed text.
Recognise one column or cell region at a time using crop, then assemble in a spreadsheet — structure survives better than full-page attempts.