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Automatic Analysis of Camera Image Data: An Example of Honey Bee (Apis cerana) Images from the Shanping Wireless Sensor Network

  • Date of declaration:2011-12-31
Sheng-Shan Lu,Michael Perry,Michael Nekrasov, Tony Fountain,Peter Arzberger,Yu-Huang Wang,CC Lin
Year
2011
Key Words
bee image, image analysis, automated identification, blob detection.
Abstract
Under an international collaborative program between the Taiwan Forestry Research Institute
(TFRI) and Pacific RIM undergraduate experience (PRIME) of San Diego University, San
Diego, CA, USA in 2010, we extended an image analysis package and applied it to honey bee
observations. In this article, we describe the results of this collaboration. A tool suitable for routine
measurements and counting tasks was developed to perform an automatic process. We applied
blob-detecting of a computer vision technique to develop this package. We then tested the tool using
images with different numbers of bees present collected from the Shanping wireless sensor
network of TFRI. We compared the times consumed between the automatic and manual processes.
Results showed that analysis of images with a low number of bees present (with an average bee
number of < 30 individuals per image) between the automatic process and manual process respectively
required 9 and 315 min. A similar results showed that analysis of images with a high number
of bees present (with an average bee number of > 30 individuals per image) between the automatic
process and manual process respectively require 23 and 409 min. Although the automatic process
overestimated bee counts by 2~21%, the tool shows significant reductions in processing times. We
concluded that the program provides a convenient way to determine the target and thus facilitate
the examination of a large volume of honey bee images from a wireless sensor network in the field.