Free Image to Text OCR
Extract editable text from photos, scans, and screenshots instantly. Powered by client-side Tesseract.js with built-in contrast and rotation preprocessing filters.
Drop your image here, or browse files
Supports JPG, PNG, WebP, BMP, and Screenshots • 100% private in-browser OCR
100% In-Browser Privacy
Images and recognized text never leave your device. The OCR neural net runs in an isolated Web Worker.
Instant Recognition
Powered by Tesseract.js v5 compiled to WebAssembly for rapid character classification.
Image Preprocessing
Enhance noisy screenshots with grayscale, contrast boost, binarization, and rotation tools.
Multi-Image Batch Support
Upload multiple document scans or screenshots and extract concatenated text cleanly.
How to Extract Text from Images with Free Online OCR
Optical Character Recognition (OCR) is the technological process of converting visual letterforms from photographs, paper scans, and screenshots into machine-readable digital text characters. Whether you need to extract text from a receipt, copy information from an unselectable infographic, or transcribe scanned textbook pages, EcrioX delivers instant in-browser transcription without software installation.
Upload Picture or Scan
Drag and drop any JPG, PNG, WebP, or screenshot into the workspace or browse your files.
Enhance & Preprocess
Apply high contrast, binarization, or rotation if the photograph is taken in dim lighting or rotated.
Copy or Download Text
Inspect the extracted text in the live editor, fix any terms, and download a .TXT file or copy to clipboard.
Tips for Achieving Maximum OCR Accuracy
- Ensure Sharp Focus: Blurry or unfocused camera photos cause letters like 'c', 'e', and 'o' to blend together. Keep camera lenses stable.
- Boost Contrast: Use our built-in High Contrast and Black & White filters to eliminate textured background paper noise.
- Straighten Orientations: If a smartphone document is rotated sideways, click the Rotate button so words read horizontally left-to-right.
- Select the Correct Language: When transcribing non-English text, select the appropriate trained language model from the dropdown.