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OCR — Image to Text

OCR text extraction from image or scanned document — free online Tesseract OCR

Extract text from photos, scanned documents, and screenshots. Supports 100+ languages via AI.

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📂 Upload Image

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Drop an image here or click to browse
JPG, PNG, WEBP — for best results use clear, high-contrast images
Choose Image

✅ Extracted Text

Source Image
Uploaded image for OCR
Extracted Text
(Text will appear here after processing)
Confidence
—
Words
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Characters
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Free OCR — Extract Text from Images Online

PDFdukan's OCR tool uses Tesseract.js — the same engine behind Google's OCR technology — to accurately extract text from photos, screenshots, and scanned documents. Supports over 100 languages including English, Arabic, Urdu, Chinese, and more. All processing happens locally in your browser with zero privacy concerns.

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100+ Languages
Extract text in any language including Arabic, Urdu, Chinese, Japanese, and all Latin scripts.
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High Accuracy
Powered by Tesseract 4.x with LSTM neural network for superior recognition accuracy.
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Copy & Export
Copy text directly to clipboard or download as a .txt file with one click.

Frequently Asked Questions

The main factors are image quality and contrast. For best results: use images at 300 DPI or higher, ensure strong contrast between text and background (dark text on white works best), avoid shadows or glare, and keep text not tilted more than 15 degrees. Printed text is recognized more accurately than handwriting.
PDFdukan's OCR uses Tesseract.js which supports over 100 languages including English, Arabic, Urdu, Hindi, Spanish, French, German, Chinese, Japanese, Korean, Portuguese, Italian, Russian, and many more. Select your document's language from the dropdown for the best recognition results.
The OCR tool processes image files (JPG, PNG, WEBP). For PDFs, first use the PDF to JPG tool to convert each page to an image, then run OCR on those images. We plan to add direct PDF OCR support in a future update.
OCR processing runs entirely in your browser using a neural network model (Tesseract LSTM). The first recognition is slower because the model needs to load (~8 MB). Subsequent recognitions on the same page session are much faster. Processing time also depends on image size — large, high-resolution images take longer to analyze.
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