Lion Cipher Lab
Extract text from images with OCR
- AI Security
- Beginner
- ~40 min
- Free · no account required
Why it matters
A screenshot, a scanned page, or a phishing image is just pixels — the text inside it cannot be searched, quoted, copied, or fed to another tool until something reads it back into real characters. That something is OCR, optical character recognition, and it is a genuinely practical skill. Security analysts hit this constantly: phishing lures are sent as flat images on purpose so text filters can't read them, evidence arrives as scans, an indicator you need is trapped in a screenshot from a report. Being able to pull the text out yourself, for free, on your own machine, without uploading…
What you'll learn
- optical character recognition (OCR)
- installing and running Tesseract
- driving Tesseract from Python with pytesseract
- reading per-word confidence scores
- image preprocessing (grayscale, threshold, upscaling)
- using OCR language packs
- knowing when OCR output must be verified
Steps in this lab
- What OCR is, in one breath
- Install Tesseract, then pytesseract
- Run OCR on your own image
- Read the output — and its confidence
- Improve a bad result with preprocessing
- Language packs: OCR only reads what it was trained for
- The limits: where OCR is wrong, and why you verify
- What you can now do that most people can't