The results of fishery investigations are used to estimate the catch size, times fish are caught, and future stock in the fish culture industry. In Tokoro, Japan, scallop farms are located on gravel and sand seabed. Seabed images are necessary to visually estimate the number of scallops of a particular farm. However, there is no automatic technology for measuring resources quantities and so the current investigation technique is the manual measurement by experts. We propose a method to extract scallop areas from images of sand seabed. In the sand field, we can see only the shelly rim because the scallop is covered with sand and opens and closes its shell while it is alive and breathing. We propose a method to extract the shelly rim areas under varying illumination, extract the scallop areas using the shelly rims based on professional knowledge of the sand field, explain the results, and evaluate the method's effectiveness.

The quantity and state of fishery resources must be known so that they can be sustained. The fish culture industry is also planning to investigate resources. The results of investigations are used to estimate the catch size, times fish are caught, and future stocks. We have developed a method for extracting scallop areas from gravel seabed images to assess fish resources and also developed an automatic system that measures their quantities, sizes, and states. Japanese scallop farms for fisheries are found on gravel and sand seabeds. The seabed images are used for fishery investigations, which are absolutely necessary to visually estimate, and help us avoid using the acoustic survey. However, there is no automatic technology to measure the quantities, sizes, and states of resources, and so the current investigation technique is the manual measurement by experts. There are varied problems in automating technique. The photography environments have a high degree of noise, including large differences in lighting. Gravel, sand, clay, and debris are also included in the images. In the gravel field, we can see scallop features, such as colors, striped patterns, and fan-like shapes. This paper describes the features of our image extracting method, presents the results, and evaluates its effectiveness.