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Visualizing Document Image Collections Using Image-Based Word Clouds

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Advances in Visual Computing (ISVC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9474))

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Abstract

In this paper, we introduce image-based word clouds as a novel tool for a quick and aesthetic overviews of common words in collections of digitized text manuscripts. While OCR can be used to enable summaries and search functionality to printed modern text, historical and handwritten documents remains a challenge. By segmenting and counting word images, without applying manual transcription or OCR, we have developed a method that can produce word or tag clouds from document collections. Our new tool is not limited to any specific kind of text. We make further contributions in ways of stop-word removal, class based feature weighting and visualization. An evaluation of the proposed tool includes comparisons with ground truth word clouds on handwritten marriage licenses from the 17th century and the George Washington database of handwritten letters, from the 18th century. Our experiments show that image-based word clouds capture the same information, albeit approximately, as the regular word clouds based on text data.

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Acknowledgments

This project is a part of q2b, From quill to bytes, a framework program sponsored by the Swedish Research Council (Dnr 2012-5743) and Uppsala university. The work is done in part as a collaboration with the Swedish Museum of Natural History (Naturhistoriska riksmuseet). We would also like to thank Alicia Fornés and the Document Analysis group of the Computer Vision Center at Universitat Autnoma de Barcelona for access to the BH2M dataset.

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Authors and Affiliations

  1. Department of Information Technology, Uppsala University, Uppsala, Sweden

    Tomas Wilkinson & Anders Brun

Authors
  1. Tomas Wilkinson
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  2. Anders Brun
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Corresponding author

Correspondence to Tomas Wilkinson .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

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

    Richard Boyle

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

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

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Wilkinson, T., Brun, A. (2015). Visualizing Document Image Collections Using Image-Based Word Clouds. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_27

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  • DOI: https://doi.org/10.1007/978-3-319-27857-5_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27856-8

  • Online ISBN: 978-3-319-27857-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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