Abstract
Detecting brown plant hopper (BPH) population in images is recently concerned to support the insect monitoring application in agriculture. Combination of this research topic and the light trap systems may help to automate the counting of BPHs falling in the traps, which is currently done manually. In this paper, a new approach to detecting BPH in images based on morphological operations will be proposed. By applying these operations appropriately, shape structure and size of the BPH in images can be identified and the number of BPHs can be counted. This allows to detect BPH in images more effective and accurate, and reduce time and effort in doing this task. In addition, we also propose a method for removing noise (inserts other than BPH) in images based on the weight and color factors. The experimental results show that the proposed approach is suited for detecting and counting BPH in images.
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Tran, A.C., Tran, N.C., Huynh, H.X. (2016). An Approach to Detecting Brown Plant Hopper Based on Morphological Operations. In: Vinh, P., Barolli, L. (eds) Nature of Computation and Communication. ICTCC 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 168. Springer, Cham. https://doi.org/10.1007/978-3-319-46909-6_6
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DOI: https://doi.org/10.1007/978-3-319-46909-6_6
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