An expert system for quality assurance of document image collections

  • Authors:

  • Roman Graf;Reinhold Huber-Mörk;Alexander Schindler;Sven Schlarb

  • Affiliations:

  • Research Area Future Networks and Services, Department Safety & Security, Austrian Institute of Technology, Austria;Research Area Intelligent Vision Systems, Department Safety & Security, Austrian Institute of Technology, Austria;Research Area Intelligent Vision Systems, Department Safety & Security, Austrian Institute of Technology, Austria,Department of Software Technology and Interactive Systems, Vienna University o ...;Austrian National Library, Austria

  • Venue:
  • EuroMed'12 Proceedings of the 4th international conference on Progress in Cultural Heritage Preservation
  • Year:
  • 2012

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Abstract

Digital preservation workflows for automatic acquisition of image collections are susceptible to errors and require quality assurance. This paper presents an expert system that supports decision making for page duplicate detection in document image collections. Our goal is to create a reliable inference engine and a solid knowledge base from the output of an image processing tool that detects duplicates based on methods of computer vision. We employ artificial intelligence technologies (i.e. knowledge base, expert rules) to emulate reasoning about the knowledge base similar to a human expert. A statistical analysis of the automatically extracted information from the image comparison tool and the qualitative analysis of the aggregated knowledge are presented.