Automatic Bluefin Tuna sizing using a stereoscopic vision system

Abstract

[EN] This article presents a non-invasive fully automatic procedure for Bluefin Tuna sizing, based on a stereoscopic vision system and a deformable model of the fish ventral silhouette. An image processing procedure is performed on each video frame to extract individual fish, followed by a fitting proce- dure to adjust the fish model to the extracted targets, adapting it to the bending movements of the fish. The proposed system is able to give accu- rate measurements of tuna snout fork length (SFL) and widths at five predefined silhouette points without manual intervention. In this work, the system is used to study size evolution in adult Atlantic Bluefin Tuna (Thunnus Thynnus) over time in a growing farm. The dataset is composed of 12 pairs of videos, which were acquired once a month in 2015, between July and October, in three grow-out cages of tuna aquaculture facilities on the west Mediterranean coast. Each grow out cage contains between 300 and 650 fish on an approximate volume of 20 000 m3.Measurements were au- tomatically obtained for the 4 consecutive months after caging and suggest a fattening process: SFL shows an increase of just a few centimetres (2%) while themaximum width (A1)shows arelative increaseofmorethan20%,mostlyinthe first 2months in farm. Moreover, a linear relation (with co- efficient of determination R2> 0.98) between SFL and widths for each month is deduced, and a fattening factor (F) is introduced. The validity of the measurements is proved by comparing 15 780 SFL measurements, obtained with our automatic system in the last month, versus ground truth data of a high percentage of the stock under study (1143 out of 1579), obtaining no statistically significant difference. This procedure could be extended to other species to assess the size distribution of stocks, as discussed in the article.