Identification and counting of live fish by image analysis

Devices called fish passes are constructed in rivers to help migratory fish get over obstacles (dams). Window panes are used to observe and count by species the fish which cross. Our goal is to automate this work by using a vision system. The images used to accomplish fish recognition and counting are taken by a video camera fitted with an electronic shutter in a backlit fish pass. The development structure is based on a micro-computer connected to an image acquisition and display system. Images, taken from a S-VHS video-tape recorder, are digitized in a 256 X 256 X 8 bit format and stored on an optical disk. The recognition operations (parameter extraction and discriminant analysis classification process) are included in a dynamic process which tracks each fish while it is in the observation field to count it. When several fish come to overlap, the situation is detected by a comparison of consecutive images and then the recognition is not achieved. The classification results obtained for the `static' recognition are 90 to 100% correct recognition, depending on the species. Furthermore, the tracking process improves these results by the temporal redundancy it generates.