• DocumentCode
    3041758
  • Title

    Complex curve tracing based on a minimum spanning tree model and regularized fuzzy clustering

  • Author

    Lam, B.S.Y. ; Yan, Hong

  • Author_Institution
    Dept. of Comput. Eng. & Inf. Technol., Hong Kong City Univ., Kowloon, China
  • Volume
    3
  • fYear
    2004
  • fDate
    24-27 Oct. 2004
  • Firstpage
    2091
  • Abstract
    The fuzzy curve-tracing (FCT) algorithm can be used to extract a smooth curve from unordered noisy data. However, the model produces good results only if the curve shape is either opened or closed. In this paper, we propose several techniques to generalize the FCT algorithm for tracing complicated curves. We develop a modified clustering algorithm that can produce cluster centers less dependent on the pre-specified number of clusters, which makes the reordering of cluster centers easier. We make use of the Eikonal equation and the Prim´s algorithm to form the initial curve, which may contain sharp corners and intersections. We also introduce a more powerful curve smoothing method. Our generalized FCT algorithm is able to trace a wide range of complicated curves, such as handwritten Chinese characters.
  • Keywords
    fuzzy set theory; pattern clustering; smoothing methods; trees (mathematics); Eikonal equation; Prim algorithm; cluster center; complex curve tracing; fuzzy clustering; fuzzy curve-tracing algorithm; spanning tree model; unordered noisy data; Clustering algorithms; Data engineering; Data mining; Handwriting recognition; Information technology; Mathematical model; Noise shaping; Partitioning algorithms; Shape; Smoothing methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2004. ICIP '04. 2004 International Conference on
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-8554-3
  • Type

    conf

  • DOI
    10.1109/ICIP.2004.1421497
  • Filename
    1421497