• DocumentCode
    390701
  • Title

    Using neural network in color classification

  • Author

    Yingjian, Qi ; Siwei, Luo ; Jianyu, Li ; Huakun, Huang

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Northern Jiaotong Univ., Beijing, China
  • Volume
    1
  • fYear
    2002
  • fDate
    28-31 Oct. 2002
  • Firstpage
    708
  • Abstract
    The artificial neural network (ANN) has widely been used in the field of pattern classification. The main task of image segmentation is to extract interesting objects placed at different locations in images, so it is a sort of pattern classification problem. It can be treated as a maximum likelihood estimation problem in a color image when represented in a color histogram. In order to improve the flexibility of the classification result in a changed environment we propose the method of training the color pattern in a neural network using the EM algorithm which is a general method for the maximum likelihood problem. An experiment proved that it is applicable and significant.
  • Keywords
    image classification; image colour analysis; image segmentation; maximum likelihood estimation; neural nets; EM algorithm; artificial neural network; color classification; color histogram; color image; image segmentation; maximum likelihood estimation problem; object extraction; pattern classification; training; Artificial neural networks; Color; Data mining; Gaussian distribution; Image segmentation; Intelligent networks; Maximum likelihood estimation; Neural networks; Pattern classification; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
  • Print_ISBN
    0-7803-7490-8
  • Type

    conf

  • DOI
    10.1109/TENCON.2002.1181372
  • Filename
    1181372