Resource management for fisheries plays a pivotal role in fostering a sustainable fisheries industry. In Japan, resource surveys rely on manual measurements by staff, incurring high costs and limitations on the number of feasible measurements. This study endeavors to revolutionize resource surveys by implementing image-recognition technology. Our methodology involves developing a system that detects individual fish regions in images and automatically identifies crucial keypoints for accurate fish length measurements. We use grounded-segment-anything (Grounded-SAM), a foundation model for fish instance segmentation. Additionally, we employ a Mask Keypoint R-CNN trained on the fish image bank (FIB), which is an original dataset of fish images, to accurately detect significant fish keypoints. Diverse fish images were gathered for evaluation experiments, demonstrating the robust capabilities of the proposed method in accurately detecting both fish regions and keypoints.

Dive fisheries are widely practiced in coastal areas worldwide owing to their minimal equipment requirements and extensive historical background. Female divers in Korea and Japan have extensive knowledge of the local coastal environment and engage in sustainable fishing practices. However, the number of divers and their catches has been declining. In this study, long-term catch and effort data were collected to investigate the reasons for the decline in the catch of the sea urchin, Hemicentrotus pulcherrimus, in Mikuni, Sakai City, Fukui Prefecture, Japan. A significant correlation was observed between catch and effort, and the main reason for the decline in catch was a reduction in fishing effort. Fishermen have voluntarily limited their fishing efforts to prevent the depletion of natural stocks, and a decrease in the number of fishermen has contributed to this reduction. In addition, regulations on catchable size and fishing season were implemented. However, natural stocks appear to have declined. Although sea urchin fisheries have been sustainably practiced for a long time, current fishery management and regulations appear inadequate. Therefore, sustainable fishing requires identifying the factors that affect stock fluctuations and updating management practices.