帮助 本站公告
您现在所在的位置:网站首页 > 知识中心 > 文献详情
文献详细Journal detailed

基于机器视觉的穴盘苗检测试验研究
Experimental Study on Detection of Plug Tray Seedlings Based on Machine Vision

作  者: ;

机构地区: 北京华农农业工程技术有限公司北京100125

出  处: 《农机化研究》 2020年第4期175-179,共5页

摘  要: 针对穴盘苗出现空穴和不合格坏苗,影响蔬菜种苗销售价格,不利于机械化移栽及后续栽培,而人工剔苗补苗费时费力的问题,提出了利用机器视觉技术检测穴盘苗空穴及不合格苗、传输检测结果的方法,为穴盘苗自动化剔除空穴与不合格苗及补苗作业提供技术基础。穴盘苗空穴及不合格苗检测硬件系统由工业相机、PC机及PLC构成,通过CKVisionBuilder软件对图像进行处理,获取每个穴孔区域的像素数量,判断幼苗状态,并将获取的判断结果传输至PLC中。试验结果表明:苗龄13天的72穴意大利生菜、白玫瑰白菜及广府1号油菜心穴盘苗坏穴的检测正确率达到95.8%以上。 In order to solve the problem of vacancy and unqualified bad seedlings in potted tray seedlings,which affect the selling price of vegetable seedlings,mechanized transplanting and follow-up cultivation,and time-consuming and laborious manual culling and filling seedlings,this paper puts forward a method of detecting vacancy and unqualified seedlings in potted Tray Seedlings by machine vision technology and transferring test results.It provides technical basis for automatic removal of bad holes and unqualified seedlings,and automatic filling.The detection hardware system of cavitation and unqualified seedlings of plug seedlings is made up of industrial cameras,PC and PLC.The image is processed by CKVisionBuilder software.It obtains the number of pixels in each hole area,is judges the seedling state,transmits the judgement result to PLC.The results showed that the correct rate of detecting bad holes in 72 seedlings of Italian lettuce,White rose cabbage and Guangfu No.1 Chinese flowering cabbage was over 95.8%.

关 键 词: 穴盘苗检测 机器视觉 阈值分割

领  域: []

相关作者

作者 王枫红
作者 罗成文

相关机构对象

机构 华南理工大学

相关领域作者