Automatic system for zebrafish counting in fish facility tanks

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.