蔬菜穴盘苗自动补苗试验台穴孔定位与缺苗检测系统  

Plug hole positioning and seedling shortage detecting system on automatic seedling supplementing test-bed for vegetable plug seedlings

作　　者：王永维[1] 肖玺泽 梁喜凤 王俊[1] 武传宇[3] 徐健康 Wang Yongwei;Xiao Xize;Liang Xifeng;Wang Jun;Wu Chuanyu;Chen Jiankang(School of Biosystems Engineering and Food Science,Zhejiang University,Hangzhou 310058,China;College of Mechanical and Electrical Engineering,China Jiliang University,Hangzhou 310018,China;College of Mechanical Engineering and Automation,Zhejiang Sci-Tech University,Hangzhou 310018,China;Yongkang Quality and Technology Supervision and Inspection Center,Yongkang 321300,China)

机构地区：[1]浙江大学生物系统工程与食品科学学院,杭州310058 [2]中国计量大学机电工程学院,杭州310018 [3]浙江理工大学机械与自动控制学院,杭州310018 [4]永康市质量技术监督检测中心,永康321300

出　　处：《农业工程学报》2018年第12期35-41,共7页Transactions of the Chinese Society of Agricultural Engineering

基　　金：中央高校基本科研业务费专项资金;浙江大学大北农学科发展和人才培养基金;国家自然科学基金资助项目(51505454);国家高技术研究发展计划(863计划)项目(2012AA10A504)

摘　　要：为了精确获得蔬菜穴盘育苗空穴信息并为自动补苗提供依据,研制了蔬菜穴盘苗自动补苗试验台。利用该试验台获取了苗龄25、35 d的拟南介穴盘苗彩色图像,对彩色图像依次进行灰度化处理、Otsu阈值分割得到幼苗和穴盘二值图;对幼苗二值图进行开运算去除噪声,提取出幼苗特征图像;将穴盘二值图去除幼苗图像并去除噪声获得穴盘特征图像,依据穴盘特征图像分别在行、列上的像素统计峰值、峰宽及穴盘规格化结构,精确确定了穴孔边界;对穴孔内幼苗图像像素统计以判定是否空穴,结果表明:25、35 d拟南芥穴盘苗有苗穴孔与无苗穴孔内像素统计值差异极显著,空穴、有苗穴判断正确率均为100%,为穴盘苗空穴自动补苗提供了精确的幼苗信息与穴孔位置。The seeds cannot fully sprout owing to the seed quality, sowing precision and environmental differences. In order to get the accurate information of the null plug holes and the boundary of plug holes and provide the basis for automatic seedling supplement device, a automatic seedling supplementing test-bed was developed with seedling shortage detecting system and seedling supplementing system as core components. The seedling shortage detection system was composed of a hardware system for image processing, which include a CMOS industrial camera, a controller and a computer, and a software system programmed in MATLAB. Color images（RGB images） of Arabidopsis plug seedlings with the age of 25 and 35 d was acquired with the automatic seedling supplementing test-bed. The grayscale images of seedlings and plug holes are obtained by graying the color images applying different linear transformations to three color components of R, G and B. Applying Otsu algorithm, binary images of the grayscale images of seedlings were obtained by threshold segmentation. Then the morphological corrosion operation and expansion operation of the binary images were carried out by the disk 2 × 2 type structure operator. By marking single connected domain, analyzing the characteristics of connected domain and removing the isolated area, the noise in the binary images were removed and the characteristic images of the seedlings were extracted from the background effectively. The feature images of plug tray were acquired by removing feature images of plug seedlings from that of the plug tray according to the extracted seedling information and de-noising. And then statistics on the peak value, peak width and standardizing structure of plug tray were made according to the row and column pixel of binary images of plug trays, so that the edges of plug holes were determined accurately. The statistics of the pixel of the seedling image in each plug hole were made to determine whether the hole was short of seedlings according to the feature images

关 键 词：农业机械 移栽 图像处理 缺苗检测 穴孔定位 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]