• DocumentCode
    536277
  • Title

    Texture image recognition based on bispectrum slice and BP neural network ensembles

  • Author

    Ding, Zhengjian ; Yu, Yasheng

  • Author_Institution
    Sch. of Comput. & Commun., Lanzhou Univ. of Technol., Lanzhou, China
  • Volume
    1
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    393
  • Lastpage
    395
  • Abstract
    To obtain the spatial relationship between three or more pixels in the texture image, bispectrum is choosen to extract texture features of the image, and it contains amplitude information and phase information of the image. Due to some problems in neural network, such as unstable classifier design, configuration, training, the research based on the ensemble of neural networks appears. Compared with a single neural network, an ensemble of neural networks has better fault tolerance and generalisation ability. In this paper, bispectrum is used to extract texture features and the neural network ensembles are used to recognize the texture images. The experimental results demonstrate that the ensemble of BP neural networks can effectively improve correct recognition rate of texture images.
  • Keywords
    backpropagation; feature extraction; image recognition; image texture; neural nets; BP neural network ensembles; amplitude information; bispectrum slice; fault tolerance; phase information; spatial relationship; texture feature extraction; texture image recognition; Instruction sets; Bispectrum; diagonal slice; neural network ensembles; texture recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-6582-8
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2010.5658582
  • Filename
    5658582