• DocumentCode
    3175391
  • Title

    Model-based shape matching with structural feature grouping

  • Author

    Nishida, Hirobumi

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Aizu Univ., Fukushima, Japan
  • Volume
    2
  • fYear
    1994
  • fDate
    9-13 Oct 1994
  • Firstpage
    599
  • Abstract
    An essential problem in online handwriting recognition is in the shape variation along with the variety of stroke number and stroke order. This paper presents a clear and systematic approach to shape matching based on structural feature grouping. To cope with topological deformations caused by stroke connection and breaking, we incorporate some aspects of top-down approaches systematically into the shape matching algorithm. The grouping of local structural features into high-level features is controlled by high-level knowledge as well as the simple geometric conditions. The shape matching algorithm requires a small number of prototypes and has the following properties from the viewpoint of online character recognition: (a) The order of strokes is free; (b) The number of strokes is free; (c) Stroke connection and breaking are allowed
  • Keywords
    character recognition; high-level features; model-based shape matching; online handwriting recognition; shape matching algorithm; shape variation; stroke number; stroke order; structural feature grouping; top-down approaches; topological deformations; Character recognition; Computer science; Data mining; Deformable models; Feature extraction; Handwriting recognition; Noise shaping; Prototypes; Structural shapes; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1994. Vol. 2 - Conference B: Computer Vision & Image Processing., Proceedings of the 12th IAPR International. Conference on
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-8186-6270-0
  • Type

    conf

  • DOI
    10.1109/ICPR.1994.577052
  • Filename
    577052