Image to Text (OCR)
Extract text from any image using on-device OCR. Supports 100+ languages, preserves line breaks, and runs entirely in your browser — nothing is uploaded to a server.
What Is OCR?
OCR stands for Optical Character Recognition. It's the technology that lets a computer read text from images — whether that's a photo of a document, a screenshot, a scanned page, or even a street sign. OCR converts the pixels that form letters into actual editable, searchable text.
How to Use This Tool
- Upload an image — drag and drop, or click to browse.
- Choose a language — pick the language of the text in the image.
- Adjust settings — page segmentation mode and preprocessing options.
- Click "Extract Text" — the OCR engine processes the image on your device.
- Copy or download the extracted text.
Supported Languages
This tool uses Tesseract.js, which supports over 100 languages. Some popular options include:
- English, Spanish, French, German, Italian, Portuguese, Dutch
- Russian, Polish, Swedish, Turkish
- Arabic, Hindi, Urdu
- Chinese (Simplified), Japanese, Korean
You can also combine languages (e.g., English + Spanish) if your image contains mixed text.
Best Practices for Accurate OCR
- High contrast — dark text on a light background works best.
- Straight text — OCR works best on horizontal text. Skew or rotation reduces accuracy.
- Good resolution — 300 DPI is ideal for scanned documents. Very small text is hard to recognize.
- Clean images — no shadows, glare, or blur.
- Isolated text — remove images, borders, and decorations around the text if possible.
- Preprocessing — the "grayscale + contrast" option can help with faded or washed-out images.
Common Use Cases
- Digitize printed documents — turn scans into editable text.
- Extract text from screenshots — grab text from images that can't be selected.
- Transcribe receipts and invoices — pull out amounts, dates, and line items.
- Read signage in photos — extract street names, signs, or labels.
- Accessibility — make image content searchable and screen-reader friendly.
- Data entry automation — convert forms and tables to structured text.
- Translate content — OCR first, then feed the text into a translator.
Page Segmentation Modes
- Auto (default) — Tesseract figures out the layout on its own. Good starting point.
- Single uniform block — for images with one big block of text.
- Single column — for a single column of text (like a book page).
- Sparse text — for scattered text (like labels or signs).
- Single line — for a single line of text (like a photo of one sentence).
- Single word — for recognizing one word.
Accuracy and Confidence
Tesseract reports a confidence score (0–100) for each recognition. Higher values mean the OCR engine was more sure of its output. Common factors that reduce confidence:
- Low resolution or blurry images
- Unusual fonts or decorative type
- Rotated or skewed text
- Handwriting (OCR is designed for printed text)
- Noisy backgrounds or low contrast
If the confidence is low, try preprocessing the image or re-capturing it with better lighting and focus.
How This Tool Protects Your Privacy
Unlike many online OCR tools, this one runs entirely in your browser. Tesseract.js is loaded once and runs on your device using WebAssembly. Your images are never uploaded to a server, never stored, and never shared.
Limitations
- Handwriting — Tesseract is designed for printed text. Handwritten notes will have poor results.
- Complex layouts — tables, multi-column documents, and mixed image+text layouts may confuse the engine.
- Special characters — very unusual symbols may not be recognized correctly.
- First-load delay — the OCR engine downloads (~2–5 MB) on first use, so expect a brief wait.
Related Tools
- Image Converter — convert between image formats.
- Image Cropper — crop to isolate text before OCR.
- Image Compressor — reduce image size.
- Text Case Converter — reformat extracted text.