Image to Text
Extract text from images free with OCR. JPG, PNG, WebP, BMP and TIFF. Handles printed text, handwriting, tables and screenshots. Copy, download or export.
Image to Text (OCR) extracts written or printed text from photographs, screenshots, and scanned images using Tesseract OCR running entirely in your browser via WebAssembly. Add a JPG, PNG, WEBP, GIF, or BMP — the engine processes the image locally, detects text regions, runs character recognition, and outputs a clean text block you can copy, edit, or download. No file is sent to a server at any point; recognition runs on your device's CPU at roughly 2-4 seconds for a clear photo and 6-12 seconds for a dense scanned page.
Browser-based OCR traditionally meant poor accuracy because Tesseract's WASM build is a full neural-network model (LSTM-based) trained on 120+ languages. This tool loads the specific language model for your document's language rather than a generic multilingual model, which improves accuracy by 10-15% for non-English text. The preprocessing pipeline applies auto-deskew (corrects images taken at an angle up to 10°), binarization (converts to black/white to improve contrast), and noise removal before feeding the image to Tesseract — critical for photos taken of printed paper under uneven lighting.
Features
- Tesseract 5 LSTM OCR engine via WebAssembly — runs fully in-browser with no upload
- 120+ language support — load the right language model for Hindi, Arabic, Chinese, Japanese, Korean, and 115 others
- Auto-deskew — corrects images taken at an angle up to ±10° before recognition
- Preprocessing pipeline — binarization, noise removal, and contrast enhancement for photos taken under uneven lighting
- Text region detection — identifies and ranks text blocks by reading order (top-left to bottom-right)
- Confidence score per word — hover to see Tesseract's confidence percentage, low-confidence words highlighted in amber
- Direct copy and download — one-click copy to clipboard or .txt download
- Handles handwritten text — accuracy varies by handwriting clarity; best for printed block letters
How to use Image to Text
- Drop your image (JPG, PNG, WEBP, GIF, BMP, TIFF) into the upload area. A preview renders immediately.
- Select the document language from the dropdown. For mixed-language documents, choose the primary language.
- Click Extract Text. The preprocessing and recognition pipeline runs locally — watch the progress bar.
- Review the extracted text in the output panel. Words with confidence below 70% are highlighted — hover them to see the confidence score and correct if needed.
- Copy the text to clipboard or click Download .txt to save the output.
Frequently asked questions
How accurate is browser-based OCR compared to Google Vision or AWS Textract?
For clearly printed text on white backgrounds, Tesseract 5 LSTM achieves 98-99% character accuracy — close to cloud OCR for standard documents. For handwriting, low-contrast scans, or unusual fonts, cloud services outperform Tesseract by 5-15%. The trade-off is privacy: browser-based means your images never leave your device.
Can it handle handwritten text?
Tesseract's LSTM model recognizes some handwriting, particularly clear block capital print. Cursive handwriting accuracy is significantly lower (50-75% depending on clarity). For dedicated handwriting recognition, consider models fine-tuned for handwriting like TrOCR — note those are larger and slower.
Does it work on screenshots?
Yes, and usually with very high accuracy (98%+) because screenshots have perfect digital rendering — no print noise, perfect contrast, no skew. Screen fonts like Calibri, Arial, and Roboto are well-represented in Tesseract's training data.
What image resolution gives the best OCR results?
300 DPI is the standard for document scanning — it gives characters large enough for the neural network to recognize clearly. Below 200 DPI, accuracy drops noticeably for small fonts. Phone camera photos of documents work well at 8MP+ resolution; close-up shots of single pages perform best.
Does it extract text from PDFs?
No — this tool handles raster images (photos, screenshots, scans). For PDFs, use the OCR PDF tool which handles the PDF-specific layer extraction and text placement workflow.