摘要
为进一步提高我国智能采摘系统的实用性与作业成功率,基于图形边缘检测技术对其进行可视化应用研究。通过合理布置采摘系统的组成结构,识别影响采摘系统的作业性能因素,得出可应用于采摘系统的图形边缘检测模型,同时针对其主要执行硬件进行功能选型,增设图形边缘检测模块,进行系统软件架构设计与控制程序输入,并进行应用试验。试验结果表明:基于图形边缘检测技术的采摘系统对于不同采摘环境下的果实识别准确率均可达到82%以上,且果实损失率大大降低,系统运行稳定可靠,具有很好的推广价值。
In order to further improve the practicability and success rate of intelligent picking system in China,the visual application of the system is studied based on the technology of graph edge detection.By reasonably arranging the composition of the picking system, identifying the factors that affect the working performance of the picking system,the edge detection model that could be applied to the picking system was obtained.At the same time, the function selection of the main executive hardware of the system was carried out,especially the graphic edge detection module was added,the system software architecture design and control program input were correspondingly carried out, the visual design of the picking system was completed on the basis of configuration item assistance,and the application test was carried out.The results showed that the picking system based on graph edge detection technology could achieve more than 82% accuracy for fruit recognition in different picking environments, and the fruit loss rate was greatly reduced, the operation of the system was stable and reliable,which would be a good reference value for the improvement of similar picking equipment and agricultural machinery equipment to intelligent development.
作者
娄焕
Lou Huan(Henan Technical Institute,Zhengzhou 450042,China)
出处
《农机化研究》
北大核心
2021年第11期200-205,共6页
Journal of Agricultural Mechanization Research
基金
河南省自然科学基金项目(BK2011204)。
关键词
采摘系统
边缘检测
可视化
功能选型
识别准确率
picking system
edge detection
visualization
function selection
recognition accuracy
