机器视觉在叶菜设施种植应用研究  

Application research of machine vision technology in leafy vegetable protected planting

作　　者：吴玉娟[1] 刘永华[1] Wu Yujuan;Liu Yonghua(School of Mechanical and Eleetrical Engineering,Jiangsu Polytechnic College of Agriculture and Forestry,Jurong,212400,China)

机构地区：[1]江苏农林职业技术学院机电工程学院,江苏句容212400

出　　处：《中国农机化学报》2020年第6期166-170,共5页Journal of Chinese Agricultural Mechanization

基　　金：江苏省农业科技自主创新资金项目(CX(16)1048);江苏农林职业技术学院项目(2017KJ26);江苏农林职业技术学院创新团队(2018KJ06)。

摘　　要：为了解决设施种植过程中叶菜长势探测识别和环境控制缺乏精确化控制手段的难题,采用机器视觉技术进行叶菜长势识别的方法,综合运用嵌入式软硬件开发技术,优化完善了图像灰度化、图像二值化、边缘检测和图像加工转换算法模型,研制开发了集实时图像采集、生长层信息处理、生理层信息处理、环境因子层控制和基础数据库等功能模块组成的环境控制系统,通过进行系统仿真验证,表明系统对群体叶菜长势识别响应时间能够达到0.1 s、精度误差不超过5%,对于推动机器视觉技术在叶菜设施种植的实践应用具有重要价值。Obtaining leafy vegetable planting growth information is an important part of realizing the intelligent management of vegetable planting facility.And machine vision technology is one of most important informational means to obtain the growth situation of leafy vegetables.In order to solve the problem of environmental control for detection and identification of leaf growth,the paper systematically summarized the application and progress of machine vision technology in leaf vegetable facility planting.Meanwhile it researched and established the model of image processing algorithm.In addition,we developed the application system,and discussed and analyzed the main development direction and trend of machine vision technology.By means of simulation experiment,it showed the system had high precision of identification of leaf growth that maximum error couldn’t exceed 5%and response time was within 0.1 seonds.It is of great significance to promote the extensive application of machine vision technology in leafy vegetable planting.

关 键 词：机器视觉 叶菜 种植 图像处理 

分 类 号：S626[农业科学—园艺学]