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
Link To Document :
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