基于计算机视觉的棉花生长监测自主导航车辆研究

为了克服农作物生长大面积遥感监测精度较低的缺陷,实现作物生长态势的自动化监测,提出了一种基于计算机视觉的自主导航作物生长监测车辆,从而有效地提高了作物生长监测的精度和自动化程度。该型自动化车辆通过导航标定线在田间对作物的生长状况进行实时跟踪监测,采用CCD数字摄像头对作物的生长状况进行图像采集,使用PC机对图像进行处理,并将图像利用通信技术传输到远程监控端,并根据图像特征数据建立了作物长势的监测和预测模型。为了验证其可行性,对作物的长势进行了实地测试,通过对叶面指数和作物生物量预测模型的测试表明:数据模型的实测值和理论值基本吻合,利用该方法可以建立多种作物的长势监测和预测模型,具有推广价值。

Autonomous Navigation Vehicle for Cotton Growth Monitoring Based on Computer Vision

In order to overcome the crops growth defect of large area with low precision of remote sensing monitoring, it proposed a crop growth situation of automation monitoring based on computer vision of autonomous navigation for crop growth monitoring vehicle.So as to effectively improve the precision and the degree of automation of the crop growth monitoring.It collected the automated vehicle navigate through the calibration line real-time tracking and monitoring in the field on crop growth status and images by CCD digital camera on crop growth status.By using PC for image processing and image and using communication technology to transmit to the remote monitoring terminal, finally, it established a monitoring and prediction model of crop growth according to the characteristics of the image data.In order to verify the feasibility, the growth of crops were field tested, by the prediction of leaf area index and crop biomass model tests,it show that the data model of measured value theory and value of the basic was both very unify.By using this method, we can establish a variety of crop growth monitoring and prediction model, the promotion of the technology.