The present work offers an innovative and automatic approach for detecting, tracking, analyzing, and reporting the natural behavior of the Varroa destructor mite and its activity from videos provided by the Tropical Apicultural Research Center (CINAT) in Costa Rica. These videos correspond to the presence of V. destructor in capped Africanized worker honeybee cells in a controlled environment. The main objective of this paper is to present an automatic report of the identification of the mite behavior based on mite information (bioinspired information). First, a calibration system was implemented to enhance the frame. This calibration was achieved by searching the movement-active area (MAA) and the geometrical definition of the V. destructor mite. Then, an automatic detection and tracking was applied. Finally, an automatic classification was used to establish the mite activity. This approach reached up to 92.83% for all processes: detection, tracking, behavior analysis, and activity reporting, in real time and showing a cognitive model of the mite. The proposed approach provides an automatic tool and objective measurement against manual and qualitative methods traditionally applied in this kind of analysis, with a significant potential to be used as a reference in the modeling of the behavior of the V. destructor mite.
Cognitive Computation – Springer Journals
Published: May 20, 2017
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