农机化研究2017，Vol.39Issue(11)：212-216,5.
基于多维特征数据库的玉米长势自动监测车辆设计
Design of Corn Growing Automatic Monitoring Vehicle Based on Multidimensional Feature Database
摘要
Abstract
In order to improve crop growth forecast accuracy and real-time performance, a binocular stereo vision is based vehicle automatic monitoring of corn growing new, and the image reconstruction of multidimensional technology is introduced into the design of the vehicle.The autonomous navigation technology is without the need for workers to enter the farmland under the condition, which can realize remote monitoring of intelligent the growth of corn.In order to solve the problem of redundant data acquisition characteristics of maize leaf area which resulted in information processing speed is not high, the dimension reduction method of LPP is improved, and the algorithm is verified by the test.The results show that by using LPP algorithm to complete the optimization of crop multidimensional feature information for dimensionality reduction, which has high practicality and accuracy.The performance of the vehicle automatic monitoring of corn growth was tested by the biomass prediction results show that the growth forecast and monitoring vehicle biomass inversion model and the measurement error is small, which verifies the feasibility of monitoring vehicle design.关键词
多维数据库/玉米长势/监测车辆/LPP降维/生物量Key words
multidimensional database/corn growth/monitoring vehicle/LPP dimension/biomass分类
信息技术与安全科学引用本文复制引用
罗元成,汪应..基于多维特征数据库的玉米长势自动监测车辆设计[J].农机化研究,2017,39(11):212-216,5.基金项目
重庆市教育委员会重点项目(1202086) （1202086）
