• DocumentCode
    2397231
  • Title

    Contrast Enhancement for Fruit Image by Gray Transform and Wavelet Neural Network

  • Author

    Zhang, Changjiang ; Wang, Xiaodong ; Zhang, Haoran

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Zhejiang Normal Univ., Jinhua
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1064
  • Lastpage
    1069
  • Abstract
    A new contrast enhancement algorithm for fruit image is proposed by gray transform and wavelet neural network (WNN). IBT is used to obtain non-linear gray transform curve. A new criterion is proposed with gray level histogram. Contrast type for original image is determined employing the new criterion. Transform parameters are determined directly by different contrast type of input image. In order to calculate non-linear gray transform in the whole image, a kind of WNN is proposed to approximate it. Experimental results show that the new algorithm is able to adaptively enhance the contrast for the image. The computation for the new algorithm is O (MN), where M and N are width and height in the original image
  • Keywords
    image enhancement; image resolution; neural nets; wavelet transforms; contrast enhancement algorithm; fruit image; gray level histogram; incomplete beta transform; nonlinear gray transform curve; wavelet neural network; Histograms; Image converters; Image edge detection; Image enhancement; Image sequences; Information science; Infrared imaging; Neural networks; Shape; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on
  • Conference_Location
    Ft. Lauderdale, FL
  • Print_ISBN
    1-4244-0065-1
  • Type

    conf

  • DOI
    10.1109/ICNSC.2006.1673299
  • Filename
    1673299