• DocumentCode
    2030647
  • Title

    A central distance method for invariant recognition of digital figures

  • Author

    Kaneko, Teruyuki ; Sagara, Tetsuo ; Takeda, Takashi ; Takiyama, Ryuzo

  • Author_Institution
    Dept. of Mech. Eng., Nagasaki Inst. of Appl. Sci., Japan
  • Volume
    3
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    1208
  • Abstract
    The authors have previously (1998, 1999) developed a description method for the recognition of non-singly connected figures using a “self-distance function” which allows for shift, scaling and rotational variation. The self-distance function is computed for all combinations of the points which make up the figures, so that the self-distance function can be calculated in O(n2) operations via an n-point figure, which is time-consuming. This paper proposes a “central distance function” to reduce the computation time. In this improved version, we measure the distances between the “centre of gravity” of the digital figure and the points making up the digital figure, so that the central distance function can be calculated in O(n) operations via an n-point digital figure. Experimental results show the usefulness of the proposed method
  • Keywords
    computational complexity; distance measurement; image recognition; invariance; central distance function; computation time; computational complexity; digital figures; invariant recognition; nonsingly connected figures; rotational invariance; scale invariance; self-distance function; shift invariance; Frequency; Genetic mutations; Gravity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-5871-6
  • Type

    conf

  • DOI
    10.1109/ICONIP.1999.844711
  • Filename
    844711