100% PrivateBrowser-Based OCR15+ Languages

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How It Works

1

Upload Image

Drop or select an image containing text you want to extract.

2

Select Language

Choose the language of the text in your image for optimal accuracy.

3

Extract & Copy

The OCR engine processes your image and extracts all readable text.

Frequently Asked Questions

What is OCR (Optical Character Recognition)?
OCR is a technology that converts different types of documents — scanned paper documents, PDF files, or photos — into editable and searchable text. It recognizes printed or handwritten characters in images and translates them into machine-readable text.
Which languages are supported?
This tool supports over 15 languages including English, French, German, Spanish, Italian, Portuguese, Dutch, Polish, Russian, Japanese, Chinese (Simplified and Traditional), Korean, Arabic, Hindi, and Turkish. Select your language before extraction for best results.
How can I improve OCR accuracy?
For best results, use high-resolution images with clear, well-lit text. Avoid blurry, skewed, or low-contrast images. Printed text with standard fonts achieves higher accuracy than handwritten text. Crop the image to focus on the text area.
What are the accuracy limitations?
OCR accuracy depends on image quality, font type, and language complexity. Printed text in common fonts can achieve 95%+ accuracy. Handwritten text, artistic fonts, or damaged documents may produce lower accuracy. Complex layouts with columns or tables may also affect results.
Can OCR recognize handwriting?
OCR can attempt to recognize handwriting, but accuracy varies significantly based on legibility. Neat, print-style handwriting is recognized better than cursive. For best results with handwriting, use high-contrast images and select the correct language.
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About Image to Text

What this tool does

Advanced image tools apply effects like blur, brightness, contrast, sepia, grayscale, vignette, pixelation, and noise. They also support background removal, color palette extraction, and image-to-text (OCR) conversion.

Why use this tool

Quick image adjustments are common when preparing visuals for presentations, social media, or print. These tools provide Photoshop-like filters without the complexity, subscription, or file-upload risk of cloud-based editors.

How it works

CSS filters and Canvas pixel manipulation handle most effects. Background removal uses edge-detection algorithms. OCR leverages Tesseract.js running in a Web Worker. Color palette extraction samples dominant colors using k-means clustering.

Pro tip

For background removal on product photos, shoot against a solid, high-contrast background. The cleaner the original, the better the automatic mask will be.

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