Vertical slot fishways are hydraulic structures which allow the up-stream migration of fish through obstructions in rivers. The appropriate design of these should consider the behavior and biological variable of the target fish species and currently existing mechanisms to measure the behavior of the fish in these assays, cuch as direct observation or placement of sensors on the speciments , are impractical or unduly affect the animal beahavior.
This paper studies the application of Artificial Neural networks to the problema of automatic fish segmentation in vertical slot sishways. In particular, SOM Neural networks have been used to detect fishes using visual information sampled by and underwater camera system. A ground true dataset was designed with expersts and different approaches were tested providing promising results.