Image to Text OCR Tool
Extract text from any image instantly. Powered by Tesseract.js v5 WebAssembly - 100% private, no server upload, works offline.
Batch OCR - Process Multiple Images
Upload up to 10 images at once. Results download as a single merged TXT file.
What is OCR? How Does Image to Text Extraction Work?
OCR (Optical Character Recognition) is a technology that recognizes and extracts text from images, scanned documents, photographs, screenshots, and PDFs. Our tool uses Tesseract.js v5, powered by a Long Short-Term Memory (LSTM) neural network that achieves state-of-the-art accuracy on printed text across multiple scripts and writing systems.
How Our Browser-Based OCR Engine Works
Unlike traditional online OCR tools that upload your images to remote servers, our tool operates entirely inside your browser using WebAssembly (WASM). Here is the complete pipeline:
- Image Upload and Scaling: Your image is loaded into browser memory and scaled to standardized resolution for optimal OCR input.
- Pre-processing Pipeline: Six optional enhancement steps (Grayscale, Auto Contrast, Gaussian Blur, Sharpening, Otsu Thresholding, and Deskewing) are applied to maximize OCR accuracy.
- Web Worker Isolation: The Tesseract WASM engine runs in a background Web Worker thread, keeping your browser UI completely smooth and responsive during recognition.
- LSTM Neural Network Recognition: The Tesseract LSTM model analyzes character sequences, producing text output with per-word confidence scores and bounding box coordinates.
- Result Rendering: Extracted text is displayed in an editable panel with word-level bounding boxes on the image. Export to TXT or Searchable PDF in one click.
OCR Accuracy Tips: Getting the Best Results
- Use high resolution: Images at 300 DPI or higher produce significantly better results than low-resolution screenshots.
- Maximize contrast: Dark text on a bright background is ideal. Enable Auto Contrast preprocessing if your image has poor contrast.
- Remove noise: Enable Denoise preprocessing for images with grain, scan artifacts, or JPEG compression noise.
- Binarize for text documents: Enable the Threshold (Otsu) step for scanned documents, receipts, or invoices.
- Fix rotation: Enable Deskew for tilted images. Tesseract performs significantly better on horizontally-aligned text.
- Select the correct language: Always select the language that matches your image content.
- Choose the right Document Type: For multi-column layouts like newspapers, select "Newspaper / Multi-Column".
Supported Languages and Accuracy Overview
| Language | Script | Direction | Data Size | Best Use Cases |
|---|---|---|---|---|
| English | Latin | LTR | ~10.4 MB | Documents, books, receipts, invoices, screenshots |
| Arabic | Arabic | RTL | ~1.6 MB | Arabic newspapers, social posts, printed Arabic documents |
| Urdu | Perso-Arabic | RTL | ~1.0 MB | Urdu printed books, news clippings, official documents |
| French | Latin | LTR | ~6.3 MB | French-language documents, menus, books |
| German | Latin | LTR | ~7.1 MB | German documents, official forms, labels |
| Spanish | Latin | LTR | ~8.4 MB | Spanish-language articles, forms, receipts |
Privacy and Security: Why Client-Side OCR Matters
Most online OCR tools upload your images to remote servers. This creates serious privacy risks since your images may contain sensitive personal information such as ID cards, medical records, or financial statements. Our tool operates entirely inside your browser. No image data, no recognized text, and no metadata ever leaves your device.
Use Cases: When You Need an OCR Tool
- Digitizing printed documents: Convert scanned PDFs, physical books, and paper forms into editable digital text.
- Processing receipts and invoices: Extract amounts, dates, and line items from scanned financial documents.
- Extracting text from screenshots: Pull text from screenshots of apps, websites, or error messages without retyping.
- Digitizing news clippings: Convert newspaper clippings into searchable digital archives.
- Research and academic work: Extract quotes from scanned academic papers and textbooks.
- Processing ID documents: Extract text from business cards and ID cards securely (fully private, no server upload).
Frequently Asked Questions (FAQ)
Yes, completely. This OCR tool runs 100% inside your browser using WebAssembly and Web Workers. Your images are never sent to any server. You can disconnect your internet after the page loads and the tool continues working fully offline.
The tool supports 6 languages: English, Arabic, Urdu, French, German, and Spanish. Language data is downloaded once on first use and cached automatically for offline access. Arabic and Urdu text is displayed right-to-left as expected.
Common causes: wrong language selected, low-resolution image, poor contrast, or image rotation. Fixes: Enable Auto Contrast, enable Threshold for text documents, enable Deskew for rotated images, and select the correct language. Use 300 DPI+ images for best results.
A Searchable PDF contains your original image as the visual layer, with an invisible OCR text layer precisely overlaid. The PDF looks exactly like your image, but you can use Ctrl+F to search for words and select or copy text using any PDF viewer.
Tesseract.js is optimized for printed, typeset text. Neat block capitals may be recognized reasonably well, but cursive or irregular handwriting typically produces poor results.
When you first run OCR with a selected language, Tesseract.js automatically downloads that language data file and stores it in your browser IndexedDB storage. On all subsequent uses, the language loads instantly from local cache without any internet connection needed.
Batch OCR lets you upload up to 10 images at once. The tool processes them one by one using your selected language and settings, showing individual progress for each file. Download all results as a single merged TXT file with each image text clearly labeled by filename.
Supported formats: JPG, PNG, WebP, BMP, TIFF, and GIF. For best results, use PNG or high-quality JPG. Avoid heavily compressed JPEGs as compression artifacts can reduce OCR accuracy significantly.