Glossary
/ OCR (Optical Character Recognition)

OCR (Optical Character Recognition)

Optical Character Recognition (OCR) is a technology that enables the extraction of text from images or scanned documents and converts it into editable, digital data. OCR is particularly useful for digitizing printed or handwritten documents and finds application in many industries.

Basics

OCR software analyzes an image and identifies characters, words, and sentences contained within it. The recognized characters are then converted into text form, which can be edited, searched, or exported to other formats such as PDF or Word. Modern OCR technologies often use machine learning and artificial intelligence to improve the accuracy of text recognition.

Advantages of OCR

  • Time savings: OCR accelerates the process of data entry and management by minimizing manual work.
  • Accuracy: OCR technology can be very accurate, especially when working with high-quality scans and clear text.
  • Accessibility: By converting printed material into digital formats, the text becomes searchable for search engines and more accessible to people with visual impairments.

Application Areas

  • Document management: Scanning and archiving contracts, invoices, and other business documents.
  • Libraries and archives: Digitization of books and manuscripts for online accessibility.
  • Automated data capture: In logistics for capturing delivery information and in manufacturing for quality control.
  • Education: Scanning and digitization of school and study materials.

Challenges

  • Quality of originals: Poorly scanned or damaged documents can affect the accuracy of OCR technology.
  • Fonts and layouts: Some OCR systems may have difficulty recognizing unusual fonts or complex layouts.
  • Language support: Not all OCR systems support multiple languages, especially those with non-Latin writing systems.

Conclusion

Optical Character Recognition is a transformative technology that increases efficiency in many areas and offers new possibilities for digitization and accessibility of information. As with any technology, there are challenges and limitations, but the ongoing development and improvement of OCR systems make it an indispensable tool in the modern data landscape. In AI-powered document analysis applications like MAIA, OCR is an essential function that can significantly improve the quality of responses.