Akademik Veri Yönetim Sistemi
2024 IEEE/SICE International Symposium on System Integration, SII 2024, Ha Long, Vietnam, 8 - 11 Ocak 2024, ss.637-643, (Tam Metin Bildiri)
With the gradual decrease in fisheries resources and the increasing demand for fishery production, the production of capture fisheries is saturated. On the other hand, aquaculture production is increasing rapidly and now accounts for almost half of all fishery production. In aquaculture, monitoring aqua cages and collecting basic information, such as the number of fish in the cages and their sizes, is one of the most crucial tasks. However, automation of these basic tasks is insufficient, and there is an expectation for the implementation of ICT (Information and Communication Technology) in the fisheries industry. To move towards smart fishery farms, efficient fisheries resource management is required. This paper introduces a computer vision-based fish counting system that utilizes image enhancement and machine learning algorithms to achieve automated fish counting in aqua cages. Experimental results demonstrate that the proposed method can detect fish and identify the same fish in images captured by underwater cameras set at different depths. The proposed method can contribute to fisheries management and ecological conservation.