Screenshot to Text (OCR)

What Is OCR?

OCR (Optical Character Recognition) is a technology that converts different types of documents — such as scanned paper documents, PDF files, or images captured by a digital camera — into editable and searchable data. Our screenshot-to-text tool uses Tesseract.js, an open-source OCR engine compiled to JavaScript, enabling text extraction directly in your browser without uploading images to any server.

This means your images stay on your device. Whether you need to extract text from a screenshot, a scanned document, a photo of a whiteboard, or a receipt, this tool handles it all with zero data leaving your browser.

How It Works

Our tool processes images entirely in your browser using a multi-step pipeline:

• Step 1 — Image Input: Drag and drop an image, click to upload, or paste from clipboard (Ctrl+V / Cmd+V). Supported formats include JPG, PNG, GIF, WebP, and BMP.
• Step 2 — Preprocessing: The image is automatically converted to grayscale and contrast-enhanced to improve recognition accuracy, especially for low-quality screenshots.
• Step 3 — Text Recognition: Tesseract.js analyzes the preprocessed image, identifying text regions, characters, and words. It supports over 100 languages out of the box.
• Step 4 — Result Output: Extracted text appears in an editable textarea. You can review, correct any misrecognitions, copy to clipboard, or download as a plain text file.

Tips for Better OCR Results

• Use high-resolution images — screenshots at 2x or 3x retina resolution produce significantly better results than low-res captures.
• Ensure good contrast — dark text on a light background (or vice versa) works best. Avoid low-contrast gradients behind text.
• Crop to the text area — removing unnecessary whitespace and non-text elements improves both speed and accuracy.
• Select the correct language — choosing the right language model in the dropdown prevents garbled output for non-English text.
• Printed text works best — while handwriting recognition has improved, printed or typed text consistently yields the highest accuracy (95%+ for clean images).

Common Use Cases

• Extract text from screenshots — copy error messages, code snippets, or UI text from screenshots without retyping.
• Digitize printed documents — convert scanned pages, book excerpts, or printed forms into editable text.
• Process receipts and invoices — extract purchase amounts, dates, and vendor names for expense tracking.
• Convert whiteboard photos — save meeting notes and brainstorm diagrams as searchable text.
• Read text from images on social media — extract captions and overlaid text from Instagram, Twitter, or LinkedIn posts.