• DocumentCode
    2225719
  • Title

    The application of Local Linear Neuro Fuzzy model in recognition of online Persian isolated characters

  • Author

    Daryoush, Koorosh Samimi ; Khademi, Maryam ; Nikookar, Alireza ; Farahani, Aida

  • Author_Institution
    South Tehran Branch, Islamic Azad Univ., Tehran, Iran
  • Volume
    5
  • fYear
    2010
  • fDate
    20-22 Aug. 2010
  • Abstract
    In this paper, we propose an approach for recognizing online Persian isolated characters using LLNF model. Local Linear Neuro Fuzzy (LLNF) Model is a powerful approach for classification tasks. It uses divide-and-conquer strategy to partition the problem space into sub-problems and construct Local Linear Models (LLMs). In order to classify the characters, at first, we extract some generic features of Persian character and build a features vector. Then we construct a LLNF model by the features vector as input data. The constructed LLNF model will be later used to recognize the written letters. Our experimental results for 100 different people show recognition rate of 99.15%.
  • Keywords
    character recognition; divide and conquer methods; feature extraction; fuzzy neural nets; natural language processing; speech recognition; divide and conquer strategy; feature vector; generic features extraction; local linear neuro fuzzy model; online Persian isolated character recognition; written letter; Handwriting recognition; LLNF; Local Linear Neuro-Fuzzy model; Online handwriting recognition; feature extraction; persian character;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2154-7491
  • Print_ISBN
    978-1-4244-6539-2
  • Type

    conf

  • DOI
    10.1109/ICACTE.2010.5579433
  • Filename
    5579433