摘要
为快速测量红枣的体积和表面积,给红枣三维信息的分级装备开发提供依据。该文搭建图像采集装置,由工业相机连续拍摄旋转圆盘上物体的二维图像,编写图像处理软件提取图像的二维轮廓特征,再由二维图像的轮廓构建三维多轮廓模型,测量模型的体积和表面积。探讨不同轮廓间角(4°~15°),不同投影高度(0.1~0.5cm)和不同直径(24~42 mm)对多轮廓模型测量体积和表面积的影响。试验结果表明,多轮廓球体模型的直径为固定值,体积的相对误差随轮廓间角和投影高度的增大而增大,表面积的相对误差随轮廓间角和投影高度的增大而减小,最小相对误差分别为6.0%和1.0%;多轮廓球体模型的轮廓间角和投影高度为确定值,模型的体积和表面积的相对误差随直径的变化不明显,但直径越小误差越大,体积和表面积相对误差的均值分别为9.1%和4.34%;多轮廓红枣模型的轮廓间角和投影高度为确定值,模型体积的平均相对误差随等级的增大而增大,表面积随等级变化不明显,其中体积的均方根误差和平均相对误差的均值为2.45 cm3和10.2%;表面积的均方根误差和平均相对误差的均值为3.65 cm^2和7.09%。红枣多轮廓模型测量方法为红枣分级装备的开发提供技术参考。
Ample sunshine, together with scarce rainfall and large variation in diurnal temperature, makes Xinjiang a unique place for producing tasty red jujube in China. Grading is an important parameter for storing and processing the jujube to maximize its market value, and needs to measure its volume and surface area. Traditional methods for measuring fruit volume are spheroid-like to measure the volume of water the fruit displaces when being immersed into water, with the surface area measured by peeling or slicing. These methods are inefficient and cannot be used for real-time measurement. The aim of this paper is to present a real-time multi-contour model to estimate the volume and surface area of the red jujube. We assessed the effect of contour angles, projection heights and diameters on the ultimate results. In the proposed method, 2 D images of the targeted jujube were captured on a rotating circular table using a camera, and the contour of the images was then extracted using image processing. A 3 D multi-contour model was developed based on the extracted2 D contour, and it was then used to estimate the volume and surface area of the targeted jujube. The result showed that the diameter of the target estimated by the multi-contour sphere model did not change, and that with an increase in the relative errors between the contours angle and the projection height, the volume estimated by the model increased(with the minimum relative error being 6.0%) while the error of the estimated surface area decreased(with the minimum being 1.0%). The angle between the contour and the projection height in the multi-contour sphere model had a prescribed value, and the relative error of the volume and surface area estimated by the model varied with the diameter in that the smaller the diameter was, the bigger the errors were. The average mean square error and the average relative error of the volume and surface area estimated by the model were 2.45 cm3 and 10.2%, and 3.65 cm^2 and 7.09%, respectively. An increase in grading appeared
作者
吴明清
弋晓康
罗华平
李传峰
唐晓燕
陈坤杰
Wu Mingqing;Yi Xiaokang;Luo Huapin;Li Chuanfeng;Tang Xiaoyan;Chen Kunjie(College of Engineering,Nanjing Agricultural University,Nanjing 210031 China;College of Mechanic and Electrical Engineering,Tarim University,Alar 843300,China;Green Food Office of Agricultural and Rural Affairs Department of Jiangsu Province,Nanjing 210036,China)
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2019年第19期283-290,共8页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家自然科学基金项目(31560479、11464039)
关键词
机器视觉
模型
分级
红枣
多轮廓模型
体积
表面积
computer vision
models
classfication
red jujube
multi contour model
volume
surface area
