• DocumentCode
    2820704
  • Title

    Identification and counting of pests using extended region grow algorithm

  • Author

    Martin, A. ; Sathish, D. ; Balachander, C. ; Hariprasath, T. ; Krishnamoorthi, G.

  • Author_Institution
    Dept. of Master Comput. Applic., Sri Manakula Vinayagar Eng. Coll., Puducherry, India
  • fYear
    2015
  • fDate
    26-27 Feb. 2015
  • Firstpage
    1229
  • Lastpage
    1234
  • Abstract
    Agriculture plays most important role in the Indian economy. The agriculture sector of India has covered about 43percent of India´s land area. Digital image processing is the use of computer algorithms like histogram, segmentation, edge detection, fuzzy approach, region based growing and tracking to perform analysis on digital images. In the existing system it is seen that there is a requirement for manual detection and extraction of pest in agricultural field which is not more efficient and accurate. In the proposed work, an integrated pest management using image processing algorithm using extended region based growing to identify the pest and have the counting of the pest to predict the pesticide amount to be used. This extended region grow algorithm provides best identification and counting of the pest.
  • Keywords
    agriculture; edge detection; fuzzy set theory; image enhancement; image segmentation; Digital image processing; Indian economy; agriculture; edge detection; extended region grow algorithm; fuzzy approach; image histogram; image segmentation; image tracking; Agriculture; Algorithm design and analysis; Image processing; Insects; MATLAB; Sociology; Statistics; agriculture; counting; detection; extended region grow; image processing; pest;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics and Communication Systems (ICECS), 2015 2nd International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4799-7224-1
  • Type

    conf

  • DOI
    10.1109/ECS.2015.7124779
  • Filename
    7124779