• DocumentCode
    2955457
  • Title

    An Automatic On-Site Fire Ant Screening System

  • Author

    Sanqiang Zhao ; Yongsheng Gao ; Caelli, Terry ; Bracco, F.

  • Author_Institution
    Queensland Res. Lab., NICTA, St. Lucia, QLD, Australia
  • fYear
    2012
  • fDate
    3-5 Dec. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper proposes the first attempt for semi-automatic screening and identification of red imported fire ants (Solenopsis invicta) in Australia. As an exotic ant species to Australia, fire ants were imported from South America in 2001 and have since been regarded as dangerous pests that could severely damage the environment and many industries. We followed two of the three major identification keys defined by entomologists and proposed: 1) A fusion of two different image features (i.e., the perpendicular median intensity and the perpendicular width) for antenna segment detection; and 2) A weighted histogramming of micropattern features for petiole classification. Our experimental results show that automatic on-site fire ant screening is feasible and the proposed weighted histogramming of micropattern features performs better than the original micropattern representation.
  • Keywords
    feature extraction; image classification; image fusion; image matching; object detection; pest control; Australia; antenna segment detection; automatic on site fire ant screening system; image fusion; micropattern feature extraction; petiole classification; red imported fire ant identification; weighted histogramming; Antennas; Australia; Feature extraction; Fires; Histograms; Image segmentation; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Image Computing Techniques and Applications (DICTA), 2012 International Conference on
  • Conference_Location
    Fremantle, WA
  • Print_ISBN
    978-1-4673-2180-8
  • Electronic_ISBN
    978-1-4673-2179-2
  • Type

    conf

  • DOI
    10.1109/DICTA.2012.6411725
  • Filename
    6411725