• DocumentCode
    227048
  • Title

    Vowel recognition system of Lipsynchrobot in lips gesture using neural network

  • Author

    Sulistijono, Indra Adji ; Baiqunni, Haikal Hakim ; Darojah, Zaqiatud ; Purnomo, Didik Setyo

  • Author_Institution
    Politek. Elektron. Negeri Surabaya (Electron. Eng. Polytech. Inst. of Surabaya), Surabaya, Indonesia
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1751
  • Lastpage
    1756
  • Abstract
    In this research, we propose a system of vowel recognition on the shape of the lips using a neural network backpropagation. For recognizing the shape of the vowels in the lips by image capturing through the webcam, and then processed through image processing which includes edge detection, filtering, mouth feature extraction, integral projection and vowels recognition on the lips using a back propagation neural network. The vowel recognition results obtained at the lips of the testing process neural network based on the training data and test data. The proposed method works well. The final results obtained from this research is a system that able to detect the lips with good features, with the success of recognizing vowels using 250 training data is 70%. The output data from the vowel recognition on the lips is used as an input to Lipsynchrobot that followed the gesture of human lips.
  • Keywords
    backpropagation; edge detection; feature extraction; gesture recognition; image capture; neural nets; shape recognition; Lipsynchrobot; edge detection; edge filtering; image capturing; image processing; integral projection; lip gesture; mouth feature extraction; neural network; neural network backpropagation; testing process; vowel recognition system; vowel shape recognition; webcam; Feature extraction; Lips; Mouth; Neural networks; Pattern recognition; Robots; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-2073-0
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2014.6891843
  • Filename
    6891843