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An Image Based Approach for Content Analysis in Document Collections

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Advances in Visual Computing (ISVC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8034))

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Abstract

We consider the task of content based analysis and categorization in large-scale historical book scanning projects. Mixed content, deprecated language, noise and unexpected distortions suggest an image based approach. The use of keypoint extractors combined with the bag of features approach is applied to scanned text documents. In order to incorporate spatial information into the bag of features approach we consider three methods of spatial verification. An approach based on comparison of statistical properties of local keypoint properties such as size orientation and scale showed comparable quality in content comparison while being computationally much more efficient. Cluster analysis delivers groups of pages characterized by common properties, especially duplicated page content is detected with high reliability.

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Author information

Authors and Affiliations

  1. Intelligent Vision Systems, Safety & Security Department, AIT Austrian Institute of Technology GmbH, Vienna, Austria

    Reinhold Huber-Mörk & Alexander Schindler

Authors
  1. Reinhold Huber-Mörk
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  2. Alexander Schindler
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Editor information

Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Arizona State University, Tempe, AZ, USA

    Baoxin Li

  6. Mitsubishi Electric Research Laboratories, Cambridge, MA, USA

    Fatih Porikli

  7. University of California, Riverside, CA, USA

    Victor Zordan

  8. AT&T Research Labs, Florham Park, NJ, USA

    James Klosowski

  9. ZIRST, Saint-Ismier Cedex, France

    Sabine Coquillart

  10. Qualcomm Research, San Diego, CA, USA

    Xun Luo

  11. Oxford e-Research Centre, University of Oxford,, Oxford, UK

    Min Chen

  12. IBM, Hawthorne, NY, USA

    David Gotz

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© 2013 Springer-Verlag Berlin Heidelberg

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Huber-Mörk, R., Schindler, A. (2013). An Image Based Approach for Content Analysis in Document Collections. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2013. Lecture Notes in Computer Science, vol 8034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41939-3_27

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  • DOI: https://doi.org/10.1007/978-3-642-41939-3_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41938-6

  • Online ISBN: 978-3-642-41939-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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