• DocumentCode
    1718251
  • Title

    A fuzzy based classification scheme for unconstrained handwritten Devanagari character recognition

  • Author

    Shelke, Sushama ; Apte, Shaila

  • Author_Institution
    Electron. & Telecommun., NBN Sinhgad Sch. of Eng., Pune, India
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The large data set and similar structural features of the characters in Devanagari script demand a highly efficient classification and recognition system. This paper presents a novel approach for the recognition of unconstrained handwritten Devanagari characters. The system is based on multi-stage classification scheme. The classification stages categorize the characters into smaller groups. The classification is done using two stages, first stage is based on fuzzy inference system and second stage is based on structural parameters. The fuzzy system improves the classification over crisp classification. The classified characters are passed to the feature extraction stage. The final stage implements feed forward neural network for character recognition. The recognition accuracy achieved by the proposed method is 96.95%.
  • Keywords
    feature extraction; feedforward neural nets; fuzzy reasoning; fuzzy systems; handwritten character recognition; natural language processing; pattern classification; character structural features; feature extraction stage; feedforward neural network; fuzzy based classification scheme; fuzzy inference system; multistage classification scheme; structural parameters; unconstrained handwritten Devanagari character recognition; Biological neural networks; Character recognition; Feature extraction; Fuzzy logic; Neurons; Training; fuzzy logic; handwritten Devanagari characters recognition; neural network; structural features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication, Information & Computing Technology (ICCICT), 2015 International Conference on
  • Conference_Location
    Mumbai
  • Print_ISBN
    978-1-4799-5521-3
  • Type

    conf

  • DOI
    10.1109/ICCICT.2015.7045738
  • Filename
    7045738