A trainable system for grading fish from images

摘要

Trainable computer vision systems are receiving increased attention in different application domains for their versatility and flexibility. This paper describes a trainable system capable of determining fish weight form image measurements. A prototype of the proposed system has been experimentally installed as a component of an automatic fish grading device at a fish farm. The image measurements are taken from top and side views of live fish sliding through a transparent channel. After the training stage, in which a support vector machine learns the relation between fish weight and shape parameters from a small number of examples, the system is able to grade fish at the rate of three fish per second. The experimental results obtained thus far and reported I the paper indicate that the system is adequate for the required task.