Can acoustic shadows identify fish species? A novel application of imaging sonar data

Abstract

Abstract This study addresses a fish species discrimination method based on normalised elliptic Fourier descriptors applied to acoustic shadows derived by Dual‐frequency Identification Sonar (DIDSON). Acoustic shadows of templates (20, 30, 40 and 50 cm) and live fish of four species [bream, Abramis brama (L.); barbel, Barbus barbus (L.); chub, Leuciscus cephalus (L.); and trout, Salmo trutta (L.)] were projected on a plate in an experimental set‐up and tested on suitability for species discrimination. Twenty‐centimetre templates were correctly classified in 97.5% of the cases, indicating a size threshold. The larger templates reached values of 100% correct classification based on cross‐validated discriminant function analysis. It was also possible to classify moving fish based on screenshots of their acoustic shadows with a certainty of 83.9%. Extended field tests are required to evaluate the method for use in practical monitoring applications in multispecies river environments.