Abstract
A proposal is described for an underwater sensor combining an acoustic device with an optical one to automatically size juvenile bluefin tuna from a ventral perspective. Acoustic and optical information is acquired when the tuna are swimming freely and the fish cross our combined sensor’s field of view. Image processing techniques are used to identify and classify fish traces in acoustic data (echogram), while the video frames are processed by fitting a deformable model of the fishes’ ventral silhouette. Finally, the fish are sized combining the processed acoustic and optical data, once the correspondence between the two kinds of data is verified. The proposed system is able to automatically give accurate measurements of the tuna’s Snout-Fork Length (SFL) and width. In comparison with our previously validated automatic sizing procedure with stereoscopic vision, this proposal improves the samples per hour of computing time by 7.2 times in a tank with 77 juveniles of Atlantic bluefin tuna (Thunnus thynnus), without compromising the accuracy of the measurements. This work validates the procedure for combining acoustic and optical data for fish sizing and is the first step towards an embedded sensor, whose electronics and processing capabilities should be optimized to be autonomous in terms of the power supply and to enable real-time processing.
Highlights
The proposal behind our study is to design dual sensors to provide some fault tolerance, energy savings and low cost in continuous monitoring
This paper presents an automatic sizing procedure based on computer vision techniques, able to accurately estimate a great number of samples using a sensor that combines acoustic and optical data
The results show that both swimming tilt tilt indicator (STI) and Convolutional Neural Network (CNN) approaches acoustic images used to train the CNN
Summary
The proposal behind our study is to design dual sensors to provide some fault tolerance, energy savings and low cost in continuous monitoring. Knowledge of the physical and biological conditions of underwater ecosystems and populations, as well as their behavior in the face of overfishing of species and noise from propellers that generate electric energy, all makes it necessary to study them in order to provide knowledge and tools for the marine authorities to legislate on how to exploit this environment in the least aggressive way possible. Optical sensors are very appropriate for developing accurate, low cost, and non-invasive methods to explore underwater ecosystems and in particular for estimating fish biomass, as demonstrated in recent years [1,2,3,4,5,6]. Optical sensors and Sensors 2020, 20, 5294; doi:10.3390/s20185294 www.mdpi.com/journal/sensors
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