融合二维关键点检测与三维结构光的多模态鱼类表型可塑性分类方法
By integrating two-dimensional keypoint detection with three-dimensional structured light, a multimodal fish phenotypic plasticity classification method was developed, which solved the problem that traditional two-dimensional vision methods are difficult to accurately capture the three-dimensional geometric details of fish bodies. This enabled accurate identification of the origin of large yellow croaker and improved the efficiency of market supervision and resource protection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- EAST CHINA SEA FISHERIES RES INST CHINESE ACAD OF FISHERY SCI
- Filing Date
- 2026-04-13
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional two-dimensional vision methods are unable to accurately capture the three-dimensional geometric details of fish, making it difficult to accurately distinguish between sea-caught and farmed large yellow croaker, thus limiting technological breakthroughs in market supervision and wildlife resource protection.
A multimodal fish phenotypic plasticity classification method integrating 2D keypoint detection and 3D structured light is proposed. By constructing a multimodal classification model, high-precision structured light 3D reconstruction technology is used to obtain the geometric information of the fish surface, and key discriminant features with statistical significance are selected to construct a logistic regression discriminant formula suitable for rapid on-site identification.
The model has achieved accurate identification of the origin of large yellow croaker, with an accuracy rate of 97.14%, providing technical support for the intelligent identification and management of aquatic resources and improving the efficiency of market supervision and resource protection.
Smart Images
Figure CN122023951B_ABST