农机化研究Issue(11)：229-233,5.
基于机器视觉黄瓜果实自动分级方法
Automatic Grading Method of Cucumber Fruits Based on Machine Vision
摘要
Abstract
To achieve the realization of grading cucumber fruit fast and accurately , we build an automation sub-base platform with the help of a camera as video acquisition module , DSP core processor as the main control module , as well as other auxiliary units like weight control and motor transport part .With reference to the national standard NY/T1587-2008 , we adopt the image processing method to extract and compute the melon length , pedicel length , diameter differ-ence , arcuate height of our cucumber fruit images , thus picking up 3 varieties 240 cucumber fruit as our test sample which contains 'Changchun Mici','Longzahuang VII'and ‘Luqiu I’.After, extract 20 samples of every variety as the image extracting data analysis and take the other 60 samples into the automation sub-base platform testing .Based on the test result , it shows: the average grade precision of the platform is 96 .7% while it can process 35 fruits per minute . Compared with the traditional manual classification , our platform has a characteristic of fast-processing , NDT, accurate and objective , which provides an important basis on applying machine vision technology into the automated classification of elliptical elongated fruit .关键词
机器视觉/图像处理/黄瓜/果实/分级/机械手Key words
machine vision/image processing/cucumber/the fruit/classification/manipulator分类
信息技术与安全科学引用本文复制引用
李明,房俊龙,乔翊博,刘超,张伶鳦,赵朝阳,栾吉玲..基于机器视觉黄瓜果实自动分级方法[J].农机化研究,2016,(11):229-233,5.基金项目
黑龙江省博士后科研启动基金项目（ LBH－Q13022）；黑龙江省教育厅科学技术研究项目 （）
