Optical Character Recognition (OCR)
Last Updated: July 29, 2026 | By Mihail Sebastian | AI Dictionary
Technology that converts text in images (scans, photos, PDFs) into machine-readable characters, turning static documents into searchable, editable data.
What is Optical Character Recognition (OCR)?
Optical character recognition (OCR) is technology that converts text in images, such as scanned pages, photos, and PDFs, into machine-readable characters. The output stops being a picture and becomes data that software can search, edit, and process.
OCR is one of the oldest computer vision tasks in production use; postal services were machine-reading addresses decades before deep learning existed.
How OCR Works
- Preprocessing: The image is straightened, denoised, and contrast-adjusted so characters stand out from the background.
- Text detection: The system locates the regions that contain text and splits them into lines and words.
- Recognition: A trained model maps character shapes to characters; modern systems use neural networks that read whole lines at once.
- Postprocessing: A dictionary or language model corrects near-misses, such as a letter “l” read as the digit “1.”
Applications of OCR
- Document digitization: Archives, libraries, and legal teams convert paper records into searchable text.
- Invoice and receipt processing: Finance systems extract amounts, dates, and vendor names to automate data entry.
- Accessibility: Screen readers speak the text OCR extracts from scanned pages and photographed signs.
- License plate reading: Toll systems and parking enforcement read plates from camera images.
Example of OCR
An accounts-payable system receives a scanned invoice. OCR extracts the vendor name, invoice number, line items, and total, and attaches a confidence score to each field.
Software matches the extracted total against the purchase order automatically. Any field below the confidence threshold routes to a person for review – a standard human-in-the-loop design, because an “8” misread as a “3” in an amount is a financial error, not a cosmetic one.
Related AI terms: Computer Vision · Image Recognition · Object Detection · Natural Language Processing
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Mihail Sebastian — Writes about AI governance, regulation, and the technology behind them. Placeholder bio — replace with a real credential line. About