Aquaculture farm provides a solution towards the overfishing phenomena. However, maintaining big scale farms manually requires going through hours of video footages to collect important information about the fishes. These footages are usually taken by an underwater camera affixed in many different ways within the farm’s cage and are manually analyzed by human operators. Since they are limited to biological restrictions, issues such as wandering attention span or human error may occur. This paper proposes a non-intrusive and automated way of extracting meaningful information such as number of fishes from underwater video footages of fishes, using image processing techniques. Experimental results shows that the system managed to achieve 74.59% accuracy for correctly counting fishes.
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