Name
Abstract | ||
|---|---|---|
For aquaculture management, aquaculture farmers require a new, inexpensive device that can obtain the size of a fish without touching them, replacing the conventional spoon-net sampling method. Conventional sampling involves the risks of physical injury and mental stress to the fish, which may affect their growth rate and mortality. Therefore, we developed methods for monitoring the size of fish, considering red sea bream (RSB) aquaculture, using commercially available cameras. This study evaluates the sample size using the estimated mean fork length value in a cage, and its value is approximately 20 samples with a 2% error rate for a fork length of greater than 30 cm. We measured the fish fork length under water in the cage using both stereo vision and net-sampling methods simultaneously. The examination demonstrated that for RSB aquaculture, the estimated values of fork length from the two methods have no statistical difference. This result implies that our stereo vision system can be effectively applied to monitor RSB growth. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.20965/jrm.2018.p0231 | JOURNAL OF ROBOTICS AND MECHATRONICS |
Keywords | Field | DocType |
stereo image measurement,aquaculture management,Pagrus major | Computer vision,Biology,Stereopsis,Artificial intelligence,Pagrus major | Journal |
Volume | Issue | ISSN |
30 | SP2 | 0915-3942 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazuyoshi Komeyama | 1 | 0 | 0.34 |
| tatsuya tanaka | 2 | 0 | 1.01 |
| Takeharu Yamaguchi | 3 | 0 | 0.34 |
| Shigeru Asaumi | 4 | 0 | 0.34 |
| Shinsuke Torisawa | 5 | 0 | 0.34 |
| Tsutomu Takagi | 6 | 0 | 0.34 |