期刊论文

Ridge recognition algorithm for leaf vegetables based on machine vision

中文

中国农业大学学报

1007-4333

2020

25

3

88-98

10.11841/j.issn.1007-4333.2020.03.11

2019NK2151:湖南省重点研发计划 CX20190526:湖南省研究生科研创新项目

本校为第一机构

针对目前叶菜类蔬菜田间作业自动化程度低,缺乏适用自主导航技术等问题,提出一种基于机器视觉的叶菜类蔬菜菜垄识别算法.利用改进超绿算法(Gray=2Cg Cr-Cb)对菜地图像进行灰度化,通过二值形态学变换和连通区域提取获得菜垄区域和边界,基于Huber损失函数进行边界曲线拟合,最终提取导航基准线.图像处理结果表明:1)本研究提出的识别算法在不同光照环境下具有较好的鲁棒性,自然综合光照条件下导航基准线提取成功率为97.5％;2)基于Huber损失函数获取到的导航基准线,平均均方根误差为0.668像素,比最小二乘法高72.5％,平均角度偏差为0.273°,比最小二乘法高72.6％,且处理速度与最小二乘法相似.试验证明...

To solve the problems of low automation and lack of autonomous navigation technology for leaf vegetables' field operations,a machine vision based ridge recognition algorithm for leaf vegetables is proposed in this study.The improved super green algorithm(Gray=2Cg-Cr-Cb)is used for gray processing the vegetable map image.The edge of vegetable ridge and boundary are extracted by binary morphological transformation combined with the extraction of connected area.The boundary curve is fitted based on Huber loss function and the navigation datum line is finally obtained.The results of image processi...