OCR a Receipt in 30 Seconds (Free, In Your Browser, No Upload)
Need to digitize a receipt, business card, or screenshot of text? Skip the SaaS sign-up. Here's the fastest free workflow — accuracy tips included — running entirely on your own machine.
Most "free OCR" services either watermark the output, cap you at three images per day, or quietly upload your receipts to their server. None of that is necessary. Modern browsers can run the full Tesseract OCR engine via WebAssembly, on your machine, in about the same time it takes to drag-and-drop the file.
The 30-second workflow
- Open Screenshot to Text in any browser.
- Drag the image (PNG, JPG, WebP, GIF, BMP, TIFF) into the dropzone.
- Wait for OCR — first run downloads ~10 MB of language data, cached afterward.
- Copy the extracted text or paste it straight into ChatGPT, Claude, or your spreadsheet.
Five tips that double your accuracy
1. Crop tight
OCR engines do better on a cropped receipt than a full phone photo. Crop out the table, the floor, anything that isn't text. Even rough cropping helps.
2. Increase contrast before OCR
A faded thermal receipt with grey text on grey paper is the OCR worst case. Open the image in any photo app, push contrast to +50, and brightness to +10 before you upload. Black-on-white is what Tesseract trained on.
3. Straighten skew
A receipt photographed at an angle confuses character segmentation. Rotate it to vertical first. Most phones do this automatically; double-check before processing.
4. Use the original resolution
Don't downscale before uploading. OCR uses pixel detail to distinguish similar characters (8 vs B, 0 vs O). The bigger the image, the better — up to about 2,400 px on the long side.
5. For multi-language receipts, expect compound errors
Tesseract loads one language model at a time. A receipt with mixed English and Korean will score 80% on English lines and near-zero on Korean. For mixed-language documents, run twice and combine.
What about handwriting?
Tesseract is trained on printed text and struggles with handwriting. For handwritten notes, a vision model like GPT-4 or Gemini will outperform OCR — paste the image directly into the chat instead of OCR'ing first. See our guide on OCR vs vision models for the full comparison.
Bulk receipts for expenses or bookkeeping
A folder of monthly receipts is a perfect job for Batch Document Extractor. Drop them all in, get a ZIP back with one text file per receipt, then have an AI total them by category. Five minutes from photos to a categorized expense report.
Tools mentioned
Frequently asked
Is browser OCR really as accurate as cloud OCR?
For printed text on a clean background, yes — both use the same Tesseract engine under the hood. For handwriting or noisy backgrounds, dedicated cloud APIs (Google Vision, AWS Textract) still win.
Why does the first OCR run take so long?
The browser downloads the language model (~10 MB for English). It's cached after that, so subsequent images process in seconds.
Can I OCR a hundred receipts at once?
Yes — use the Batch Document Extractor. Drop all the images in, walk away, come back to a ZIP.
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