• DocumentCode
    2041502
  • Title

    Peanut Shape Recognition Based on Fourier Descriptor

  • Author

    Chen Hong ; Zeng Chuanhua ; Ding Youchun

  • Author_Institution
    Eng. & Technol. Coll., Huazhong Agric. Univ., Wuhan
  • fYear
    2009
  • fDate
    23-24 May 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A sort of software for peanut shape identification based on artificial neural network was developed. Images of peanut which is advantageous for carries on the characteristic extraction were acquired by means of red component extraction, filter, image division, edge examination, and so on. The method to describe the shape of irregular peanut was studied, in which the Fourier transform and Fourier inverse transform were applied. It was concluded that the first thirteen harmonics of the Fourier descriptor were enough to represent the primary shape of peanut, The method achieved an accuracy of 90% for oblong peanuts, 93.3% for simple peanuts, 96.7% for trilateral peanuts, 100% for elliptic peanuts and 93.3% for circular peanuts.
  • Keywords
    Fourier transforms; edge detection; feature extraction; neural nets; object recognition; Fourier descriptor; Fourier inverse transform; Fourier transform; artificial neural network; edge examination; image division; peanut shape recognition; red component extraction; Agricultural engineering; Agricultural products; Color; Computer vision; Educational institutions; Electronic mail; Fourier transforms; Kernel; Materials testing; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-3893-8
  • Electronic_ISBN
    978-1-4244-3894-5
  • Type

    conf

  • DOI
    10.1109/IWISA.2009.5073005
  • Filename
    5073005