• DocumentCode
    2950925
  • Title

    Tracking Multiple Insects Using Multilayer Feed-Forward Networks

  • Author

    Kumar, N. Ravi ; Janakiraman, T.N. ; Thiagarajan, Hemalatha ; Subaharan, K.

  • Author_Institution
    Nat. Inst. of Technol., Trichy
  • fYear
    2008
  • fDate
    4-6 Jan. 2008
  • Firstpage
    417
  • Lastpage
    421
  • Abstract
    In the present study, attempts are made to capture and track coconut black headed caterpillar, Opisina arenosella and its parasitoid, Goniozus nephantidis with respect to their path and orientation. We devised an automatic tracking system using Artificial Neural Network for tracking both insects. The tracking system is based on the extracted features of the insects. Using the geometry of the image we have proposed a method to separate the two insects when they are joined in the image in the course of their motion. A fixed multilayer feed-forward backpropagation network (FMFBPN) was employed to solve the correspondence problem between frames. After establishing correspondence, the traced paths are plotted and length of the path of each insect is computed.
  • Keywords
    backpropagation; biology computing; feature extraction; image motion analysis; image segmentation; image sequences; multilayer perceptrons; Goniozus nephantidis; Opisina arenosella; artificial neural network; automatic tracking system; coconut black headed caterpillar; geometry; image segmentation; image sequence; multilayer feed-forward network; Artificial neural networks; Computer networks; Crops; Feature extraction; Feedforward systems; Insects; Mathematics; Nonhomogeneous media; Shape; Video compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communications and Networking, 2008. ICSCN '08. International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4244-1924-1
  • Electronic_ISBN
    978-1-4244-1924-1
  • Type

    conf

  • DOI
    10.1109/ICSCN.2008.4447230
  • Filename
    4447230