LAUSR

Abstract Fish size inspection is becoming increasingly important in aquaculture applications and research including growth monitoring, an early indication of health problems and others. However, sizing of small fish has not yet been thoroughly explored in the literature due to challenges associated with rapid and unpredictable changes in the swimming direction of such fish. This paper presents a new low-cost computer vision system for estimating the length of small fish length using dual synchronized orthogonal webcams. The contour and location of the fish body are identified through continuous capturing of front and side images of the fish population under study. A mathematical model that accounts for the projection error that is mainly caused by the depth from the camera and light refraction is derived and implemented in this study. An automatic calibration procedure is also suggested to account for light-refraction during the fish length measurements. Similarly, a camera distance calibration is performed experimentally and considered throughout the estimation process of the fish length. The performance of the developed vision system is assessed experimentally using individual free-swimming adult zebrafish. The obtained results for the subjects under test have demonstrated an average estimation error of approximately 1%. Such a relatively high estimation performance demonstrates the validity of the proposed model and compares favourably to the state of the art of small-fish sizing.