水产学报2024，Vol.48Issue(12)：51-60,10.DOI:10.11964/jfc.20240114331
基于双目立体视觉方法的鱼类三维重建技术
3D reconstruction of fish based on binocular vision:a case study of Scomberomorus niphonius
摘要
Abstract
Fish are an important source of dietary protein for humans,contributing significantly to national food security and public health.The body size of fish holds significant guiding and practical value for both aquaculture and marine fishing industries.With the advancement of computer vision,non-contact measurement methods are gradually replacing traditional labor-intensive manual measurements to acquire fish morphological characteristics.However,current computer vision methods cannot construct complete three-dimensional models of fish,failing to meet the current demand in the aquaculture sector for three-dimensional digital models of fish.this study utilized structured light projection combined with binocular stereovision methods to reconstruct three-dimensional digital models of fish.A fish point cloud acquisition system was designed,incorporating deep learning networks for fish body image segmentation during the acquisition process.Phase-shifting was used to mark the grayscale on the sur-face of fish bodies,and finally,a binocular stereovision system was employed to reconstruct fish point clouds.The accuracy of the system was validated using the economically important mackerel species(Scomberomorus niphonius).Results indicated that this method could construct fish point cloud models,with relative errors for fork length,body height,maximum body circumference,and posterior gill cover circumference of the reconstructed mackerel models being 0.82%,4.47%,3.14%and 2.87%,respectively.Correlation analysis and fitting of the rela-tionships between body measurements showed that the multivariate linear regression method(R2=0.826/0.833)out-performed linear regression methods.This study provides a methodological reference for digital information col-lection in the fisheries industry.关键词
蓝点马鲛/鱼类三维重建/深度学习/体尺测量Key words
Scomberomorus niphonius/fish 3D reconstruction/deep learning/fish body measurement分类
农业科技引用本文复制引用
徐安康,黄六一,尤鑫星,毕春伟,何舒玥,徐鑫乐,王笑..基于双目立体视觉方法的鱼类三维重建技术[J].水产学报,2024,48(12):51-60,10.基金项目
国家重点研发计划(2023YFD2401301) （2023YFD2401301）
山东省重点研发计划(2021SFGCO701) （2021SFGCO701）
青岛市科技计划(23-1-3-hysf-2-hy) National Key Research and Development Program of China(2023YFD2401301) （23-1-3-hysf-2-hy）
Key R&D Program of Shandong Province,China(2021SFGCO701) （2021SFGCO701）
Qingdao Science and Technology Plan(23-1-3-hysf-2-hy) （23-1-3-hysf-2-hy）
