• DocumentCode
    2963068
  • Title

    Using Neural Network to Model the Relationship between Plant Surface Color and its Pigment

  • Author

    Qingmao, Zeng ; Tong, Zhang ; Tonglin, Zhu

  • Author_Institution
    Instn. of Agric. Multimedia Technol., South China Agric. Univ., Guangzhou, China
  • Volume
    2
  • fYear
    2011
  • fDate
    28-29 March 2011
  • Firstpage
    303
  • Lastpage
    307
  • Abstract
    Combining the intelligent algorithm such as BP neural network and support vector maching (SVM) with traditional chemical method, this paper models the relationship between plant surface color and its pigment. Using the neural network model constructed above, people can figure out the content of plant pigments by getting the corresponding plant surface color information. Compared with the traditional modeling methods, this method can significantly save time and experimental supplies. Furthermore, it is easy to implement because it needn´t touch samples and doesn´t cause any damage to samples. So this method provides a practical tool for non-destructive measurements of plant pigments and solutions to explore the mystery of plant color.
  • Keywords
    agricultural products; agriculture; backpropagation; image colour analysis; neural nets; support vector machines; BP neural network model; Chinese kale stems; chemical method; plant pigments; plant surface color; support vector maching; Artificial neural networks; Data models; Image color analysis; Machine vision; Pigments; Support vector machines; Training; BP neural network; Chinese kale stems; HSV mean; Support vector machine (SVM); plant pigment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
  • Conference_Location
    Shenzhen, Guangdong
  • Print_ISBN
    978-1-61284-289-9
  • Type

    conf

  • DOI
    10.1109/ICICTA.2011.361
  • Filename
    5750886