Image to Text (OCR)

Extract text from images instantly in your browser. Supports 24+ languages with high accuracy. 100% private.

Drop an image here or click to browse

JPG, PNG, WebP, BMP — any size

Recognition Languages

1/3 selected

Extracted text will appear here

Upload an image and click "Extract Text" to begin

Pro Tips for Better OCR

  • Use high-resolution images (300 DPI+) for best accuracy
  • Enable "Enhance Contrast" for faded or low-contrast text
  • Convert to "Grayscale" to improve recognition on colored backgrounds
  • Rotate images so text is perfectly horizontal for best results
  • Select the correct language(s) to improve recognition accuracy
  • Crop to only the text area before uploading for faster processing

What is OCR? A Complete Guide to Optical Character Recognition

Optical Character Recognition (OCR) is one of the most transformative technologies in document processing. It converts images containing text — photographs, scanned documents, screenshots, and more — into editable, searchable, machine-readable text. The global OCR market is valued at $13.4 billion and is growing rapidly as businesses digitize their workflows.

How OCR Works

Modern OCR engines like Tesseract (which powers this tool) use a multi-stage process. First, the image is preprocessed: converted to grayscale, binarized (black and white), and cleaned of noise. Next, the engine identifies text regions and segments individual characters. Finally, a neural network trained on millions of text samples recognizes each character and produces the output text. Tesseract supports over 100 languages and achieves 99%+ accuracy on clean, printed text.

How to Extract Text from Images

Using this tool is straightforward: upload or paste an image, select the language(s) of the text, and click "Extract Text." The OCR engine processes the image entirely in your browser — nothing is uploaded to any server. For best results, start with a high-quality image where the text is clearly visible and properly oriented.

If your image has low contrast or colored backgrounds, enable the "Enhance Contrast" or "Grayscale" toggles in the image preview panel. These preprocessing steps can dramatically improve recognition accuracy, especially on photographs of documents taken in poor lighting.

Tips for Better OCR Accuracy

Image resolution matters. The ideal resolution for OCR is 300 DPI or higher. Lower-resolution images produce blurry characters that are harder to recognize. If you are scanning a document, set your scanner to at least 300 DPI.

Orientation is critical. OCR engines expect text to be horizontal. If your image is rotated or skewed, use the rotation buttons in the preview panel to correct it before extraction. Even a slight tilt can reduce accuracy.

Contrast and lighting. Dark text on a light background produces the best results. Photographs taken in dim lighting or with shadows across the text will have lower accuracy. The contrast enhancement toggle can help compensate for poor lighting.

Language selection. Always select the correct language(s) for your document. The OCR engine uses language-specific character sets and word dictionaries to improve accuracy. For documents containing multiple languages, you can select up to three languages simultaneously.

Common OCR Use Cases

Digitizing printed documents: Convert paper documents, books, and articles into editable digital text. This is the most common use case for OCR, enabling search, editing, and archiving of physical documents.

Extracting text from screenshots: Copy text from images, screenshots, or presentations where the text cannot be directly selected. Simply paste a screenshot and extract all the text instantly.

Processing receipts and invoices: Extract line items, totals, and dates from photographs of receipts and invoices for expense tracking and accounting.

Translating foreign text: Photograph text in a foreign language, extract it with OCR, then paste it into a translation tool. This is faster than typing unfamiliar characters manually.

Accessibility: Convert images of text into actual text that can be read by screen readers, making visual content accessible to people with visual impairments.

Privacy and Security

Unlike most online OCR tools that upload your images to remote servers for processing, this tool runs Tesseract.js entirely in your browser. Your images never leave your device. This makes it safe for sensitive documents including financial records, medical documents, legal contracts, and personal identification. There is no server infrastructure to be hacked or breached — your data stays on your machine and disappears when you close the tab.

Frequently Asked Questions

What is OCR and how does it work?
OCR (Optical Character Recognition) is technology that converts images of text into machine-readable text. It works by analyzing character shapes and patterns in an image, matching them against trained neural network models. Our tool uses Tesseract.js, a powerful open-source OCR engine developed by Google that supports 100+ languages and achieves 99%+ accuracy on clean printed text.
Is my image uploaded to a server for processing?
No. All OCR processing happens entirely in your browser using Tesseract.js (a WebAssembly-based OCR engine). Your image never leaves your device — it is never uploaded, transmitted, or stored on any server. This makes it safe for sensitive documents. When you close the tab, the image is removed from browser memory.
What languages does this OCR tool support?
This tool supports 24+ languages including English, Spanish, French, German, Portuguese, Italian, Chinese (Simplified), Japanese, Korean, Arabic, Hindi, Russian, Polish, Dutch, Turkish, Vietnamese, Thai, Ukrainian, Czech, Romanian, Hungarian, Swedish, Indonesian, and Hebrew. You can select up to 3 languages simultaneously for multi-language documents.
How accurate is the text recognition?
On clean, high-resolution images of printed text, accuracy typically exceeds 95-99%. Accuracy depends on several factors: image resolution (300 DPI+ is ideal), text clarity, font type, and background contrast. Handwritten text recognition is significantly less accurate. Enable contrast enhancement and grayscale options to improve results on difficult images.
Can I extract text from a photo taken on my phone?
Yes. You can take a photo directly using your phone's camera by tapping the upload area, or upload an existing photo from your gallery. For best results, ensure the document is well-lit, the text is in focus, and the image is not skewed. Use the rotate and contrast enhancement features to improve accuracy.
Does this tool work with handwritten text?
Tesseract.js is primarily optimized for printed text and achieves the highest accuracy on typed or printed documents. Handwritten text recognition is possible but accuracy varies significantly based on handwriting legibility. Very neat, print-style handwriting may produce usable results, while cursive or messy handwriting will have low accuracy.

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