Abstract
In this project we propose a computer vision method, based on background subtraction, to estimate the number of zebrafish inside a tank. We addressed questions related to the best choice of parameters to run the algorithm, namely the threshold blob area for fish detection and the reference area from which a blob area in a threshed frame may be considered as one or multiple fish. Empirical results obtained after several tests show that the method can successfully estimate, within a margin of error, the number of zebrafish (fries or adults) inside fish tanks proving that adaptive background subtraction is extremely effective for blob isolation and fish counting.
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Acknowledgments
This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference UID/CEC/50021/2013.
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Silvério, F.J. et al. (2016). Automatic System for Zebrafish Counting in Fish Facility Tanks. In: Campilho, A., Karray, F. (eds) Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science(), vol 9730. Springer, Cham. https://doi.org/10.1007/978-3-319-41501-7_86
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DOI: https://doi.org/10.1007/978-3-319-41501-7_86
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