• DocumentCode
    595012
  • Title

    Document segmentation using Relative Location Features

  • Author

    Fernandez, F.C. ; Terrades, O.R.

  • Author_Institution
    Comput. Vision Center, Univ. Autonoma de Barcelona, Barcelona, Spain
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    1562
  • Lastpage
    1565
  • Abstract
    In this paper we evaluate the use of Relative Location Features (RLF) on a historical document segmentation task, and compare the quality of the results obtained on structured and unstructured documents using RLF and not using them. We prove that using these features improve the final segmentation on documents with a strong structure, while their application on unstructured documents does not show significant improvement. Although this paper is not focused on segmenting unstructured documents, results obtained on a benchmark dataset are equal or even overcome previous results of similar works.
  • Keywords
    document image processing; feature extraction; image segmentation; RLF; document structure; historical document segmentation; relative location feature; Adaptation models; Computational modeling; Frequency domain analysis; Image segmentation; Labeling; Minimization; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460442