Towards automated monitoring of adult zebrafish

Over the last two decades, zebrafish (Danio rerio) have emerged as an efficient model to aid in the research of a broad range of human diseases as well as such diverse applications as environmental modelling and drug discovery. Economically, the large number, low price and low maintenance requirements of this fish species encouraged its use for research. In addition to this, the study of zebrafish is being used to improve the understanding of fish physiology, with implications for fish welfare. In order to thoroughly model the behaviour, development and growth of these fish, it is important to be able to scrutinise the characteristics of individual fish as they respond to a range of stimuli, and to this end off-line fish recognition and on-line tracking using video data is employed. Tracking and identifying such small and fast-moving objects is a challenge, and this paper seeks to address this using a behavioural analysis approach. Utilising single high resolution camera and two low-cost synchronised video cameras, the proposed systems captures front (face) and side (profile) pictures of each isolated fish as they swim past a given marker. The acquired images are then subject to three separate processing routes in order to satisfy three complementary but distinct objectives. Initially, fish face and profile features are extracted to aid the identification of individual fish. Then, for each fish identified, behavioural features such as the frequency and intensity of the operculum beat rate or breathing cycle are quantified in order to assess aspects of the fish welfare. Additionally, the volume of each fish is estimated based on its profile dimensions, enabling the weight of the fish to be monitored throughout its lifetime. This paper presents preliminary experimental considerations and findings of this on-going research project. Results to date have been both encouraging and promising, validating the approach and the experimental configuration adopted.