What is OCR?
OCR stands for Optical Character Recognition. In simple terms, it is the technology that converts images of text (like a photo of a document or a scanned PDF) into actual, machine-readable text formats (like string data, JSON, or a .txt file).
Without OCR, a photo of a page is just a grid of colored pixels to a computer. With OCR, that grid becomes data you can search, edit, and store.
How does it work?
Modern OCR engines uses pattern recognition and Machine Learning to identify the shapes of letters and numbers, even if the font is weird or the lighting is bad.
4 Real-World Use Cases
1. Expense Management
🧾 Instead of manually typing data from receipts into Excel, an app uses OCR to scan the photo, extract the Total Amount, Date, and Merchant Name, and automatically logs the expense.
2. Identity Verification (KYC)
🆔 When you sign up for a banking app and upload your Driver's License, OCR reads your name, birthdate, and ID number to verify your identity instantly without a human reviewing it.
3. License Plate Recognition
(ANPR) 🚗 Smart parking lots use cameras with OCR to read your license plate number as you enter and exit, calculating your parking fee automatically.
4. Accessibility
🦾 Screen readers can’t read pixels. OCR tools scan images on a website, extract the text inside them, and read it aloud for visually impaired users.
Conclusion
OCR is the bridge between the physical "paper" world and the digital "data" world. If you are building an app that needs to digitize manual data entry, you probably need an OCR library (like Tesseract.js or Google Vision API) in your stack!
Top comments (0)