Estimating Dimensions of Free-Swimming Fish Using 3D Point Distribution Models

Monitoring the growth of farmed fish is an important task which is currently difficult to carry out. An underwater stereo image analysis technique offers the potential for estimating key dimensions of free-swimming fish, from which the fish mass can be estimated. This paper describes the development of a three-dimensional point distribution model to capture the typical shape and variability of salmon viewed from the side. The model was fitted to stereo images of test fish by minimizing an energy function, which was based on probability distributions. The minimization was an iterated two-step method in which edges were selected for magnitude, direction, and proximity to the model, and the model was then fitted to the edges. A search strategy for locating the edges in 3D was devised. The model is tested on two image sets. In the first set 19 of the 26 fish are located in spite of their variable appearance and the presence of neighboring fish. In the second set the measurements made on 11 images of fish are compared with manual measurements of the fish dimensions and show an average error in length estimation of 5%.