Optical Character Recognition (OCR)

Definition

Optical Character Recognition (OCR) is the process of converting printed or handwritten text in images into machine-readable digital text.

Purpose

The purpose is to digitize documents for search, editing, and analysis. OCR supports applications in digitization, accessibility, and data entry automation.

Importance

  • Enables conversion of paper to searchable text.
  • Improves efficiency in industries like banking and healthcare.
  • Struggles with poor-quality scans or unusual fonts.
  • Forms the basis for text mining in scanned archives.

How It Works

  1. Scan or capture image of text.
  2. Preprocess image to remove noise.
  3. Detect and segment characters or words.
  4. Recognize text using ML models.
  5. Output editable digital text.

Examples (Real World)

  • Google Cloud Vision OCR: text recognition service.
  • ABBYY FineReader: commercial OCR software.
  • Project Gutenberg digitization: OCR for books.

References / Further Reading

  • Smith, R. “An Overview of the Tesseract OCR Engine.” ICDAR.
  • ISO/IEC 15938-4: Multimedia Content Description Interface.
  • IEEE Transactions on Pattern Analysis and Machine Intelligence.