• DocumentCode
    594963
  • Title

    2D shape recognition using biological sequence alignment tools

  • Author

    Bicego, Manuele ; Lovato, Pietro

  • Author_Institution
    Comput. Sci. Dept., Univ. of Verona, Verona, Italy
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    1359
  • Lastpage
    1362
  • Abstract
    In this paper a novel 2D shape recognition approach is proposed. The main idea is to exploit in this context the huge amount of work carried out by bioinformati-cians in the biological sequence analysis research field. In the proposed approach, we encode shapes as biological sequences, employing standard and well established sequence alignment tools to devise a similarity score, finally used in a nearest neighbour scenario. Despite its simplicity, obtained results on standard datasets are really encouraging.
  • Keywords
    bioinformatics; image coding; shape recognition; 2D shape recognition approach; bioinformaticians; biological sequence alignment tools; biological sequence analysis research field; nearest neighbour scenario; shape encoding; standard datasets; Bioinformatics; Biological information theory; Hidden Markov models; Pattern recognition; Shape; Standards;
  • 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
    6460392