• DocumentCode
    479492
  • Title

    Slant Classification Using FuzzySIS

  • Author

    Shamsuddin, M.R. ; Ibrahim, Zaidah ; Mohamed, Azlinah

  • Author_Institution
    Fac. of Inf. Technol. & Quantitative Sci., Univ. Teknol. MARA, Shah Alam
  • Volume
    1
  • fYear
    2008
  • fDate
    11-13 Nov. 2008
  • Firstpage
    1080
  • Lastpage
    1085
  • Abstract
    This paper covers the area of signature recognition and fuzzy logic. It addresses the usage of fuzzy logic to be applied in signature slant recognition. Signature slant is vaguely identifiable and hard to determine for its slant form, in this study, the aim is to distinguish right slant, left slant and vertical slant. As fuzzy can deal with vague and ambiguous terms, it is applied to solve this problem. Based on 66 acquired signatures, the fuzzy range is identified. Then, a fuzzy slant identification system (FuzzySIS) is created. Identifiable slant degrees are extracted using a slant identification algorithm to yield an input for the created fuzzy systems. The result is then tested for its accuracy with an available 100 sample of proofed signatures. The result shows a favorable accuracy of 81% correct slant identification. It is hoped that implementation would be able to give some degree of contribution in the area of signature recognition and fuzzy logic.
  • Keywords
    fuzzy logic; fuzzy systems; handwriting recognition; FuzzySIS; fuzzy logic; fuzzy systems; signature recognition; signature slant recognition; slant classification; Fuzzy logic; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Humans; Inference algorithms; Information technology; Size measurement; Testing; Writing; fuzzy; fuzzy logic; signature feature; slant; slant identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Convergence and Hybrid Information Technology, 2008. ICCIT '08. Third International Conference on
  • Conference_Location
    Busan
  • Print_ISBN
    978-0-7695-3407-7
  • Type

    conf

  • DOI
    10.1109/ICCIT.2008.381
  • Filename
    4682177