• DocumentCode
    2306695
  • Title

    Linear Discriminant Analysis and Its Application in Plant Classification

  • Author

    Du, Minggang ; Wang, Xianfeng

  • Author_Institution
    Sch. of Urban & Environ. Sci., Shanxi Normal Univ., Linfen, China
  • fYear
    2011
  • fDate
    25-27 April 2011
  • Firstpage
    548
  • Lastpage
    551
  • Abstract
    The most common organisms on Earth are plants, which are crucial to the maintenance of atmospheric composition, nutrient cycling and other ecosystem processes. The classification of plants is vital to the study of plant genetic diversity and ecological sensitivity, which is also helpful for many problems such as feeding the population and fighting disease. In this paper, we firstly discuss the shortages of LDA, then classify the plant by using PCA+LDA. The experiments show that it is effective and feasible for plant classification.
  • Keywords
    diseases; ecology; genetic engineering; horticulture; image classification; principal component analysis; production engineering computing; atmospheric composition; common organisms; disease; ecological sensitivity; ecosystem processes; linear discriminant analysis; nutrient cycling; plant classification; plant genetic diversity; principal component analysis; Algorithm design and analysis; Classification algorithms; Feature extraction; Pattern recognition; Personal digital assistants; Shape; Support vector machines; Dimension reduction; LDA; Plant classification; Small-sample-size problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Computing (ICIC), 2011 Fourth International Conference on
  • Conference_Location
    Phuket Island
  • Print_ISBN
    978-1-61284-688-0
  • Type

    conf

  • DOI
    10.1109/ICIC.2011.147
  • Filename
    5954627