About OCR Tool
Professional text extraction from images and PDFs
OCR (Optical Character Recognition) Tool is a professional, browser-based application for extracting text from images and PDF documents. Powered by Tesseract.js v5 WebAssembly, all processing happens entirely client-side, ensuring complete data privacy.
The tool supports over 10 languages including English, Hindi, Spanish, French, German, Chinese, Japanese, and Arabic. Advanced image preprocessing options like contrast enhancement, grayscale conversion, and sharpening help achieve optimal accuracy even on low-quality scans.
How to Use
1 Upload Your File
Upload Methods:
- Drag & Drop: Drag image or PDF directly onto the upload area
- Click to Browse: Click "Select File" button to open file picker
- Supported Formats: JPG, PNG, WebP, BMP, GIF, PDF
2 Configure Settings
Options Available:
- Language: Select the language of text in your document
- Boost Contrast: Improves visibility of faded text
- Grayscale: Removes color noise for better accuracy
- Sharpen: Enhances edge definition for blurry images
3 Process & Download
After Processing:
- Copy: Copy extracted text directly to clipboard
- Download TXT: Save as plain text file
- Download DOCX: Save as Word document
Use Cases
Document Digitization
Convert printed documents, receipts, and invoices into editable digital text for archiving and data entry automation.
Academic Research
Extract text from scanned textbooks, research papers, and historical documents for citation and analysis purposes.
Translation Prep
Extract text from foreign language documents before running translation. Supports Hindi, Chinese, Japanese, Arabic, and more.
Screenshot Text Extraction
Extract text from screenshots, social media images, and memes. Perfect for copying text that you cannot select.
Identity Document Processing
Extract information from ID cards, passports, and licenses locally without uploading sensitive documents to external servers.
Invoice & Receipt Processing
Extract line items, totals, and vendor information from invoices and receipts for accounting and expense tracking.
Technical Capabilities
Powered by Tesseract.js v5 WebAssembly Engine
This OCR tool leverages Tesseract.js version 5, the most advanced WebAssembly-based optical character recognition engine available for browsers. Tesseract is originally developed by HP Labs and later maintained by Google, representing over two decades of OCR research and development. The WebAssembly compilation ensures near-native performance while maintaining complete browser compatibility across Chrome, Firefox, Safari, and Edge.
The engine utilizes Long Short-Term Memory (LSTM) neural networks trained on millions of text samples across over 100 languages. For Latin-based scripts like English, Spanish, French, and German, accuracy rates typically exceed 95% on clean printed text. Non-Latin scripts including Hindi (Devanagari), Chinese (Simplified and Traditional), Japanese (Kanji, Hiragana, Katakana), Arabic, and Russian (Cyrillic) are fully supported with specialized training data.
Image preprocessing capabilities include contrast enhancement using histogram equalization, grayscale conversion for noise reduction, edge sharpening using convolution kernels, and color inversion for light-on-dark text scenarios. These preprocessing steps can significantly improve recognition accuracy on low-quality scans, photographs, and screenshots. The tool automatically detects text orientation and applies deskewing algorithms when necessary.
PDF processing utilizes PDF.js, Mozilla's open-source PDF rendering library, to convert each page into high-resolution canvas images at 2x scale factor before OCR analysis. This approach ensures consistent text extraction even from scanned PDF documents that contain no embedded text layer. Multi-page documents are processed sequentially with per-page progress tracking.
Frequently Asked Questions
How accurate is the OCR text extraction?
Accuracy depends primarily on image quality and text clarity. High-resolution scans of printed documents typically achieve 95-99% accuracy. Lower quality images like photos or screenshots may yield 80-90% accuracy. Using the image enhancement options (Boost Contrast, Grayscale, Sharpen) can significantly improve results on poor quality source images. Handwritten text recognition is experimental with variable results depending on legibility.
Is my data private and secure?
Absolutely. This tool runs 100% in your browser using WebAssembly technology. Your files are never uploaded to any server. All OCR processing happens locally on your device using your CPU. We have zero access to your documents. This makes it safe for processing sensitive documents like ID cards, financial statements, and confidential business documents.
What languages are supported for OCR?
We support over 10 major languages including English, Hindi (Devanagari script), Spanish (Español), French (Français), German (Deutsch), Italian (Italiano), Portuguese (Português), Russian (Cyrillic), Japanese (Kanji, Hiragana, Katakana), Chinese Simplified (简体中文), and Arabic (العربية). Language-specific trained data is downloaded on-demand for optimal file size efficiency.
Can I extract text from multi-page PDF documents?
Yes! The tool fully supports multi-page PDF documents. Each page is rendered to a high-resolution image and processed individually. The extracted text from all pages is combined with clear page separators. Processing time scales linearly with page count - expect approximately 5-15 seconds per page depending on complexity and your device's processing power.
What image formats are supported?
The OCR tool supports all common image formats including JPG/JPEG, PNG, WebP, BMP, and GIF. For best results, use high-resolution images (300 DPI or higher for scanned documents). PNG format is recommended for screenshots as it preserves sharp text edges without compression artifacts that can occur with JPEG.
Why is the first OCR extraction slower?
The first extraction requires downloading the Tesseract OCR engine core (approximately 2MB) and language-specific training data (1-10MB depending on language). This data is cached in your browser, so subsequent extractions will be significantly faster. The initial download only happens once per language.
Can I process handwritten text?
Handwritten text recognition (HTR) is supported but with variable accuracy. Clear, print-style handwriting on plain backgrounds works best. Cursive handwriting, stylized fonts, and low-contrast writing may produce poor results. For critical documents, we recommend verifying and correcting the extracted text manually after processing.