Detection of candidate areas for automatic identification of scirtothrips dorsalis

CB Moon, BM Kim, JY Yi, JW Hyun… - Journal of the Korea …, 2012 - koreascience.kr
CB Moon, BM Kim, JY Yi, JW Hyun, PH Yi
Journal of the Korea Industrial Information Systems Research, 2012koreascience.kr
Abstract Scirtothrips Dorsalis (Thysanoptera: Thripidae) recently has been recognized as a
major source of the pest damage in the citrus fruit orchards. So its arrival has been predicted
periodically but it is difficult to identify adults of the pest with the naked eyes because of their
size smaller than the 0.8 mm. In this paper, we propose a method to detect candidate areas
for automatic identification of Scirtothrips Dorsalis on forecasting traps. The proposed
method uses a histogram-based template matching where the composite image synthesized …
Abstract
Scirtothrips Dorsalis (Thysanoptera: Thripidae) recently has been recognized as a major source of the pest damage in the citrus fruit orchards. So its arrival has been predicted periodically but it is difficult to identify adults of the pest with the naked eyes because of their size smaller than the 0.8 mm. In this paper, we propose a method to detect candidate areas for automatic identification of Scirtothrips Dorsalis on forecasting traps. The proposed method uses a histogram-based template matching where the composite image synthesized with the gray-scale image and the gradient image is used. In our experiments, images are acquired by the optical microscopy with 50 magnifications. To show the usefulness of the proposed method, it is compared with the method we previously suggested. Also, the performances when the proposed method is applied to noise-reduced images and gradient images are examined. The experimental results show that the proposed method is approximately 14.42% better than our previous method, 41.63% higher than the case that the noise-reduced image is used, and 21.17% higher than the case that the gradient image is used.
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