摘要
【目的】随着林业信息化的快速发展,机器视觉测量技术广泛应用于林业领域。针对传统立木因子测量方法成本较高、携带不便、操作复杂等问题,提出消费级双目相机与机器视觉技术相结合的立木因子无接触测量方法。【方法】首先使用消费级USB 3.0双目相机采集立木图像,通过改进的SGM算法生成高质量视差图;再根据三角原理转化为深度图,进而获取立木三维点云;基于空间密度聚类和混合滤波三维点云去噪方法快速准确去除聚集、离散的噪声点,再进行方向矫正和点云分割;最后,利用最值遍历法和椭圆拟合法实现树高、胸径的无接触测量。【结果】树高、胸径的相对测量误差分别小于2.219%、5.620%,测量值与真实值的相关系数R2分别为0.978、0.995,均方根误差分别为0.047 m、0.249 cm。【结论】本方法易操作、成本较低,同时具有较高的测量精度,能够满足无接触测量的需求。
[Objective]With machine vision measurement technology being widely used in the field of forestry as a result of the rapid development of forestry informatization,this study is aimed to propose a contact less tree attribute measuring method combining consumer binocular-grade camera and machine vision technology to replace the traditional one which is featured with high cost,low mobility and complicated operation.[Method]Firstly,a consumer-grade USB 3.0 binocular camera was used to capture images of tree before a high-quality parallax image was generated by an improved SGM algorithm.Then it was transformed into a depth image in accordance with the triangulation principle so as to obtain a 3D point cloud.Next,the three-dimensional point cloud denoising method based on spatial density clustering and hybrid filtering was employed to remove the aggregated and discrete noise points quickly and accurately after which orientation correction and point cloud segmentation were performed.Finally,the most-valued traversal method and ellipse fitting method were used to achieve contactless measurement of tree height and DBH(diameter at breast height).[Result]The relative measurement errors of tree height and DBH were less than 2.219%and 5.620%,with the correlation coefficients being 0.918 and 0.995,whereas the root mean square errors being 0.047 m and 0.249 cm respectively.[Conclusion]The proposed method in this paper,featured as convenient with low cost and high precision,can meet the requirements of contactless measurement.
作者
尹萍
徐爱俊
叶俊华
夏芳
王泽华
YIN Ping;XU Aijun;YE Junhua;XIA Fang;WANG Zehua(College of Mathematics and Computer Science,Zhejiang A&F University,Hangzhou 311300,Zhejiang,China;Zhejiang Provincial Key Laboratory of Forestry Intelligent Monitoring and Information Technology,Zhejiang A&F University,Hangzhou 311300,Zhejiang,China;Key Laboratory of National Forestry and Grassland Administration on Forestry Sensing Technology and Intelligent Engineering,Zhejiang A&F University,Hangzhou 311300,Zhejiang,China;College of Environment and Resources,Zhejiang A&F University,Hangzhou 311300,Zhejiang,China;Institute of Digital Country,Zhejiang A&F University,Hangzhou 311300,Zhejiang,China;College of Economics and Management,Zhejiang A&F University,Hangzhou 311300,Zhejiang,China)
出处
《浙江农林大学学报》
CAS
CSCD
北大核心
2023年第2期436-445,共10页
Journal of Zhejiang A&F University
基金
国家自然科学基金资助项目(31670641)
浙江省科技重点研发计划项目(2018C02013)
浙江省公益基金项目(LGN21C160004)。
关键词
视差图
双目视觉
三维点云
点云去噪
立木因子测量
parallax image
binocular vision
three-dimensional point cloud
point cloud denoising
tree attributes measurement
