Discrimination of contaminated fish responses by fractal dimension and entropy algorithms

Abstract

The aim of the work was to develop a non-invasive methodology for image acquisition, processing and nonlinear trajectory analysis of the center of the fish group as a response to a stochastic event. Object detection and motion estimation were performed by an optical flow algorithm. The Fractal Dimension (FD) and the Entropy of the trajectory followed by the centroids of the groups of fish were calculated using Katz, Higuchi and Katz-Castiglionís FD and the Shannon Entropy algorithms respectively. The methodology was tested on three single cases European sea bass, two of which were similar (C1 control and C2 tagged fish) and very different from the third (C3, tagged fish in methylmercury contaminated water). Katz-Castiglioni and Shannon entropy were the most sensitive algorithms and proved to be promising tools for the non-invasive identification and quantification of differences in fish responses.