Automatic length estimation of free-swimming fish using an underwater 3D range-gated camera

TLDR

Camera-based estimation of fish size is essential for aquaculture and fisheries to support data-driven decision making and biomass estimation at individual and population levels. The study proposes using an underwater 3D range‑gated camera to accurately estimate the lengths of free‑swimming fish. The system employs a fully automated, in‑situ pipeline that detects, tracks, and measures fish without manual intervention or contact, and demonstrates accuracy on free‑swimming fish. The method achieves length estimation errors of about 1 % relative to manual measurements, validating its precision for individual and population assessments.

Abstract

Camera estimation of fish size in aquaculture production and fisheries is crucial for enabling knowledge-based decision making. Automatic estimation of fish lengths on an individual and population basis are key steps to automate biomass estimation. We propose to use an underwater 3D range-gated camera for accurate fish-length estimation of free-swimming fish. The proposed algorithm requires no manual work or contact with the fish and is done in-situ. A robust algorithmic pipeline consisting of detection, tracking and fish length estimation stages is proposed. We show the accuracy of the proposed system on free-swimming fish, both in terms of individual fish lengths as well as the population distributions. The results show that the proposed system achieves length estimation errors in the order of 1% of manual-measured fish length.