农业机械学报2024，Vol.55Issue(5)：218-225,8.DOI:10.6041/j.issn.1000-1298.2024.05.020
遮挡条件下多视角甜椒果实点云三维重构方法
Multi Perspective Point Cloud Reconstruction Method for Sweet Pepper Fruit under Occlusion Conditions
摘要
Abstract
The in-situ phenotype of sweet pepper is an important reference indicator for fruit breeding and management.Automated measurement of phenotype in-situ through phenotype collection robots is one of the effective ways for digital breeding and management of sweet pepper.However,fruit occlusion during the measurement process seriously affects the success rate of detection.Therefore,a three-dimensional reconstruction method for multi view sweet pepper fruit point cloud was proposed to address the problem of target occlusion in in-situ fruit phenotype measurement.By using the method of virtual leaves,an enhanced dataset was created,and a sweet pepper fruit recognition model based on YOLO v5 algorithm was established to recognize fruits with different degrees of occlusion.At the same time,a fruit phenotype collection algorithm considering fruit position and occlusion degree was constructed to achieve multi view three-dimensional data collection of fruits.Finally,the three-dimensional point cloud of sweet pepper fruit was registered,the phenotype parameters of sweet pepper was extracted,and the effectiveness of the point cloud reconstruction method was validated through the greenhouse sweet pepper fruit phenotype.Compared with manual measurement data,the average relative error of fruit width was 1.72％,and the average relative error of fruit height was 1.60％.The experimental results indicated that the in-situ phenotype point cloud reconstruction method proposed for sweet pepper can provide effective solutions and feasible methods for crop phenotypes under occlusion conditions.关键词
甜椒/表型/数据增强/遮挡条件/点云三维重构/YOLO v5Key words
sweet pepper/phenotype/data augmentation/occlusion conditions/point cloud three-dimensional reconstruction/YOLO v5分类
信息技术与安全科学引用本文复制引用
王昱,易振峰,谭文超,郭金菊,周星星,赵俊宏..遮挡条件下多视角甜椒果实点云三维重构方法[J].农业机械学报,2024,55(5):218-225,8.基金项目
国家自然科学基金面上项目(32372002)、广东省农业科学院协同创新中心项目(XT202201)、广东省重点领域研发计划项目(2023B0202090001)、广东省农业科学院学科团队建设项目(202130TID)和广东省农业科学院科技人才引进专项资金项目(R2019YJ-YB3003) （32372002）
