高级检索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于智能手机单目视觉的多株立木高度提取方法

陈相武 徐爱俊

陈相武, 徐爱俊. 基于智能手机单目视觉的多株立木高度提取方法[J]. 北京林业大学学报, 2020, 42(8): 43-52. doi: 10.12171/j.1000-1522.20190345
引用本文: 陈相武, 徐爱俊. 基于智能手机单目视觉的多株立木高度提取方法[J]. 北京林业大学学报, 2020, 42(8): 43-52. doi: 10.12171/j.1000-1522.20190345
Chen Xiangwu, Xu Aijun. Height extraction method of multiple standing trees based on monocular vision of smart phones[J]. Journal of Beijing Forestry University, 2020, 42(8): 43-52. doi: 10.12171/j.1000-1522.20190345
Citation: Chen Xiangwu, Xu Aijun. Height extraction method of multiple standing trees based on monocular vision of smart phones[J]. Journal of Beijing Forestry University, 2020, 42(8): 43-52. doi: 10.12171/j.1000-1522.20190345

基于智能手机单目视觉的多株立木高度提取方法

doi: 10.12171/j.1000-1522.20190345
基金项目: 国家自然科学基金项目(31670641),浙江省科技重点研究计划资助项目(2018C02013)
详细信息
    作者简介:

    陈相武。主要研究方向:林业信息技术。Email:791569410@qq.com 地址:311300浙江省杭州市临安区浙江农林大学信息工程学院

    责任作者:

    徐爱俊,博士,教授。主要研究方向:资源与环境信息系统。Email:xuaj1976@163.com 地址:同上

  • 中图分类号: S758.4

Height extraction method of multiple standing trees based on monocular vision of smart phones

  • 摘要:   目的  提出一种智能手机单目视觉下的多株立木高度提取方法。  方法  该方法以智能手机为采集设备,利用Graph Cut 算法对输入的立木图像进行分割定位,实现单幅图像中多株立木轮廓的自动获取;再通过智能手机相机对摄像头进行标定,从而基于几何相似法获取智能手机相机图像的深度信息。在不同角度下拍摄标靶,进行深度提取模型的精度优化,进而确定信息提取的最优方位。同时,结合高精度陀螺仪获取相机俯视角,根据提取的深度信息和相机俯视角实现非接触条件下的多株立木高度测量。  结果  使用型号为MI 2S的小米智能手机为试验设备,在本方法中的立木高度测量模型具有良好的稳定性,并且试验中最高相对误差为2.45%,树高测量精度可达97.55%。  结论  基于智能手机单目视觉下的立木高度提取方法精确度高、操作简便,能够有效满足国家森林资源二类调查中对于树高测量精度的要求。

     

  • 图  1  深度信息几何推导

    Figure  1.  Geometric derivation of depth information

    图  2  图像坐标系与像素坐标系转换

    Figure  2.  Transformation between image coordinate system andpixel coordinate system

    图  3  深度信息模型验证

    Figure  3.  Verification of depth information model

    图  4  多株立木成像图

    Figure  4.  Imaging of multiple standing trees

    图  5  误差分析图

    Figure  5.  Chart of error analysis

    图  6  三维误差点云分布图

    Figure  6.  Point cloud distribution map of 3D error

    图  7  外业树高测量结果

    Figure  7.  Measurement results of field tree height

    表  1  深度信息测量数据

    Table  1.   Measurement data of depth information

    俯视角
    Top view angle
    γ)/(°)
    试验编号
    Experiment No.
    像素行
    Pixel row (v
    实际距离
    Actual distance/cm
    测量距离
    Measuring distance/cm
    视场角
    Field of view angle
    β)/(°)
    相对误差
    Relative error/%
    40 1 3 224 88.00 82.234 − 17.697 0.044
    2 3 293 92.40 86.593 − 18.717 0.041
    3 3 360 96.80 91.168 − 19.696 0.041
    4 3 422 101.20 95.738 − 20.591 0.041
    5 3 477 105.60 100.096 − 21.377 0.039
    30 1 2 589 92.40 86.316 − 7.831 0.013
    2 2 651 96.80 90.794 − 8.825 0.013
    3 2 705 101.20 95.012 − 9.687 0.011
    4 2 753 105.60 99.040 − 10.449 0.007
    5 2 803 110.00 103.546 − 11.239 0.007
    20 1 2 025 101.20 94.866 1.359 − 0.015
    2 2 071 105.60 98.672 0.606 − 0.020
    3 2 117 110.00 102.754 − 0.148 − 0.022
    4 2 156 114.40 106.456 − 0.786 − 0.028
    5 2 197 118.80 110.610 − 1.458 − 0.029
    10 1 1 636 112.50 115.664 7.686 0.028
    2 1 674 117.00 120.082 7.074 0.026
    3 1 713 121.50 124.962 6.443 0.028
    4 1 750 126.00 129.952 5.844 0.031
    5 1 779 130.50 134.137 5.374 0.028
    0 1 1 121 127.60 131.466 15.759 0.030
    2 1 151 132.00 135.588 15.303 0.027
    3 1 181 136.40 139.976 14.845 0.026
    4 1 210 140.80 144.496 14.400 0.026
    5 1 238 145.20 149.147 13.969 0.027
    下载: 导出CSV

    表  2  立木高度测量数据表

    Table  2.   Measuring data of standing tree height

    试验编号
    Experiment No.
    实际值
    Actual value/m
    距离
    Distance/m
    俯视角
    Top view angle/(°)
    测量值
    Measured value/m
    相对误差
    Relative error/%
    1 4.176 6 1.11 4.121 1.32
    2 4.176 6 1.11 4.188 0.29
    3 4.176 6 1.11 4.126 1.19
    4 5.109 6 − 5.45 5.049 1.17
    5 5.109 6 − 5.45 5.383 5.36
    6 5.109 6 − 5.45 5.269 3.13
    7 5.109 6 − 8.11 4.873 4.61
    8 5.109 6 − 8.11 5.167 1.14
    38 5.109 14 15.41 4.912 3.86
    39 5.109 14 15.41 4.967 2.78
    40 8.161 14 2.89 8.002 1.95
    41 8.161 14 2.89 8.050 1.36
    42 8.161 14 2.89 7.936 2.76
    43 11.998 14 − 5.81 11.461 4.48
    44 11.998 14 − 5.81 11.598 3.34
    45 11.998 14 − 5.81 11.514 4.04
    下载: 导出CSV

    表  3  树高计算结果误差分析

    Table  3.   Error analysis on calculating results of tree height

    树高
    Tree height/m
    株数
    Plant number
    平均绝对误差
    Mean absolute error/m
    平均相对误差
    Mean relative error/%
    3 ~ 6 9 0.13 2.79
    6 ~ 9 10 0.17 2.22
    9 ~ 12 11 0.23 2.29
    12 ~ 15 17 0.34 2.56
    > 15 13 0.38 2.39
    总计 Total 60 0.27 2.45
    下载: 导出CSV
  • [1] 罗朝沁, 林辉, 孙华, 等. 基于MODIS影像大尺度森林资源信息提取方法研究[J]. 中南林业科技大学学报, 2015, 35(11):21−26, 42.

    Luo C Q, Lin H, Sun H, et al. Based on MODIS image large-scale forest resources information extraction method[J]. Journal of Central South University of Forestry & Technology, 2015, 35(11): 21−26, 42.
    [2] He J S. Carbon cycling of Chinese forests: from carbon storage, dynamics to models[J]. Science China Life Sciences, 2012, 55(2): 188−190. doi: 10.1007/s11427-012-4285-z
    [3] Sellers P J, Mintz Y, Sud Y C, et al. A simple biosphere model (SIB) for use within general-circulation models[J]. Journal of the Atmospheric Sciences, 1986, 43(6): 505−531. doi: 10.1175/1520-0469(1986)043<0505:ASBMFU>2.0.CO;2
    [4] Hauglin M, Hansen E H, Næsset E, et al. Accurate single-tree positions from a harvester: a test of two global satellite-based positioning systems[J]. Scandinavian Journal of Forest Research, 2017, 32(8): 774−781. doi: 10.1080/02827581.2017.1296967
    [5] Olivier M D, Robert S, Fournier R A. A method to quantify canopy changes using multi-temporal terrestrial lidar data: tree response to surrounding gaps[J]. Agricultural and Forest Meteorology, 2017, 237−238: 184−195. doi: 10.1016/j.agrformet.2017.02.016
    [6] Ahmed O S, Shemrock A, Chabot D, et al. Hierarchical land cover and vegetation classification using multispectral data acquired from an unmanned aerial vehicle[J]. International Journal of Remote Sensing, 2017, 38(8/10): 2037−2052.
    [7] 王佳, 张隆裕, 吕春东, 等. 基于地面激光雷达点云数据的树种识别方法[J]. 农业机械学报, 2018, 49(11):180−188. doi: 10.6041/j.issn.1000-1298.2018.11.021

    Wang J, Zhang L Y, Lü C D, et al. Tree species identification methods based on point cloud data using ground-based LiDAR[J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(11): 180−188. doi: 10.6041/j.issn.1000-1298.2018.11.021
    [8] 张雄清, 张建国, 段爱国. 基于贝叶斯法估计杉木人工林树高生长模型[J]. 林业科学, 2014, 50(3):69−75.

    Zhang X Q, Zhang J G, Duan A G. Tree-height growth model for Chinese fir plantation based on bayesian method[J]. Scientia Silvae Sinicae, 2014, 50(3): 69−75.
    [9] 刘鲁霞, 庞勇, 李增元. 基于地基激光雷达的亚热带森林单木胸径与树高提取[J]. 林业科学, 2016, 52(2):26−37.

    Liu L X, Pang Y, Li Z Y. Individual tree DBH and height estimation using terrestrial laser scanning (TLS) in a subtropical forest[J]. Scientia Silvae Sinica, 2016, 52(2): 26−37.
    [10] Persson H J, Fransson J E S. Comparison between TanDEM-X- and ALS-based estimation of aboveground biomass and tree height in boreal forests[J]. Scandinavian Journal of Forest Research, 2017, 32(4): 306−319. doi: 10.1080/02827581.2016.1220618
    [11] 沈鹏, 汪长城, 朱建军, 等. 融合升降轨的极化干涉SAR三层模型植被高度反演方法[J]. 测绘学报, 2017, 46(11):1868−1879. doi: 10.11947/j.AGCS.2017.20170122

    Shen P, Wang C C, Zhu J J, et al. Vegetation height inversion method with three-layer model by fusing the ascending and descending PolInSAR data[J]. Acta Geochimica Sinica, 2017, 46(11): 1868−1879. doi: 10.11947/j.AGCS.2017.20170122
    [12] 冯仲科, 黄晓东, 刘芳. 森林调查装备与信息化技术发展分析[J]. 农业机械学报, 2015, 46(9):257−265. doi: 10.6041/j.issn.1000-1298.2015.09.038

    Feng Z K, Huang X D, Liu F. Forest survey equipment and development of information technology[J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(9): 257−265. doi: 10.6041/j.issn.1000-1298.2015.09.038
    [13] Thamrin N M, Arshad N H M, Adnan R, et al. Enhanced technique for cylindrical object diameter measurement via low-cost and innovated rotational non-intrusive sensor[C]// IEEE 10th International Colloquium on Signal Processing and its Applications (CSPA). Kuala Lumpur: IEEE, 2014.
    [14] 瞿帅, 张晓丽, 朱程浩, 等. 机载激光雷达森林资源调查系统的设计与试验[J]. 西北林学院学报, 2018, 33(4):175−182. doi: 10.3969/j.issn.1001-7461.2018.04.29

    Qu S, Zhang X L, Zhu C H, et al. Design and test of airborne LiDAR system for forest resources survey[J]. Journal of Northwest Forestry University, 2018, 33(4): 175−182. doi: 10.3969/j.issn.1001-7461.2018.04.29
    [15] Corona P, Fattorini L, Franceschi S, et al. Estimation of standing wood volume in forest compartments by exploiting airborne laser scanning information: model-based, design-based, and hybrid perspectives[J]. Canadian Journal of Forest Research, 2014, 44(11): 1303−1311. doi: 10.1139/cjfr-2014-0203
    [16] Tomppo E, Kuusinen N, Mäkisara K, et al. Effects of field plot configurations on the uncertainties of ALS-assisted forest resource estimates[J]. Scandinavian Journal of Forest Research, 2016, 32(6): 488−500.
    [17] 王宁宁, 尹文广, 黄秦军, 等. 三维扫描技术在获取杨树树冠结构特征参数上的应用[J]. 林业科学, 2015, 51(5):108−116.

    Wang N N, Yin W G, Huang Q J, et al. Application of 3D scanner technology to analysis the crown architecture parameters of poplar plantations[J]. Scientia Silvae Sinicae, 2015, 51(5): 108−116.
    [18] Díaz-Varela R A, De La Rosa R, León L, et al. High-resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: application in breeding trials[J]. Remote Sensing, 2015, 7(4): 4213−4232. doi: 10.3390/rs70404213
    [19] 邓向瑞, 冯仲科, 马钦彦, 等. 三维激光扫描系统在立木材积测定中的应用[J]. 北京林业大学学报, 2007(增刊2): 74−77.

    Deng X R, Feng Z K, Ma Q Y, et al. Application of 3D laser scanning system in mensurating standing volume[J]. Journal of Beijing Forestry University, 2007(Suppl.2): 74−77.
    [20] 郭彩玲, 宗泽, 张雪, 等. 基于三维点云数据的苹果树冠层几何参数获取[J]. 农业工程学报, 2017, 33(3):175−181. doi: 10.11975/j.issn.1002-6819.2017.03.024

    Guo C L, Zong Z, Zhang X, et al. Apple tree canopy geometric parameters acquirement based on 3D point clouds[J]. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(3): 175−181. doi: 10.11975/j.issn.1002-6819.2017.03.024
    [21] Zarco-Tejada P J, Diaz-Varela R, Angileri V, et al. Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods[J]. European Journal of Agronomy, 2014, 55: 89−99. doi: 10.1016/j.eja.2014.01.004
    [22] 张晓莉, 赵鹏祥, 高凌寒, 等. 基于ArboLiDAR的林分自动分割研究与应用[J]. 中南林业科技大学学报, 2017, 37(11):76−83.

    Zhang X L, Zhao P X, Gao L H, et al. Research and application of stand automatic segmentation based on ArboLiDAR[J]. Journal of Central South University of Forestry & Technology, 2017, 37(11): 76−83.
    [23] Panagiotidis D, Abdollahnejad A, Surový P, et al. Determining tree height and crown diameter from high-resolution UAV imagery[J]. International Journal of Remote Sensing, 2017, 38(8/10): 2392−2410.
    [24] Holzmann C, Hochgatterer M. Measuring distance with mobile phones using single-camera stereo vision[C]// 32nd International Conference on Distributed Computing Systems Workshops. Macau: IEEE, 2012: 88−93.
    [25] Chen S W, Fang X Y, Shen J B, et al. Single-image distance measurement by a smart mobile device[J]. IEEE Transactions on Cybernetics, 2016, 47(12): 4451−4462.
    [26] 周克瑜, 汪云珍, 李记, 等. 基于Android平台的测树系统研究与实现[J]. 南京林业大学学报(自然科学版), 2016, 40(4):95−100.

    Zhou K Y, Wang Y Z, Li J, et al. A study of tree measurement systems based on Android platform[J]. Journal of Nanjing Forestry University (National Sciences Edition), 2016, 40(4): 95−100.
    [27] Han D Y, Wang C D. Tree height measurement based on image processing embedded in smart mobile phone[C]// International Conference on Multimedia Technology. Hangzhou: IEEE, 2011.
    [28] 邱梓轩, 冯仲科, 蒋君志伟, 等. 森林智能测绘记算器设计与试验[J]. 农业机械学报, 2017, 48(5):179−187. doi: 10.6041/j.issn.1000-1298.2017.05.022

    Qiu Z X, Feng Z K, Jiang J Z W, et al. Design and experiment of forest intelligent surveying and mapping instrument[J]. Transactions of the Chinese Society for Agricultural Machinery, 2017, 48(5): 179−187. doi: 10.6041/j.issn.1000-1298.2017.05.022
    [29] 徐伟恒, 冯仲科, 苏志芳, 等. 手持式数字化多功能电子测树枪的研制与试验[J]. 农业工程学报, 2013, 29(3):90−99.

    Xu W H, Feng Z K, Su Z F, et al. Development and experiment of handheld digitalized and multi-functional forest measurement gun[J]. Transactions of the Chinese Society for Agricultural Engineering, 2013, 29(3): 90−99.
    [30] 王佳, 杨慧乔, 冯仲科, 等. 利用轻小型飞机遥感数据建立人工林特征参数模型[J]. 农业工程学报, 2013, 29(8):164−170.

    Wang J, Yang H Q, Feng Z K, et al. Model of characteristic parameter for forest plantation with data obtained by light small aerial remote sensing system[J]. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(8): 164−170.
    [31] 管昉立, 徐爱俊. 基于智能手机与机器视觉技术的立木胸径测量方法[J]. 浙江农林大学学报, 2018, 35(5):892−899. doi: 10.11833/j.issn.2095-0756.2018.05.014

    Guan F L, Xu A J. Tree DBH measurement method based on smartphone and machine vision technology[J]. Journal of Zhejiang A&F University, 2018, 35(5): 892−899. doi: 10.11833/j.issn.2095-0756.2018.05.014
    [32] 杨婷婷, 管昉立, 徐爱俊. 基于Graph Cut算法的多株立木轮廓提取方法[J]. 南京林业大学学报(自然科学版), 2018, 42(6):91−98.

    Yang T T, Guan F L, Xu A J. Multiple trees contour extraction method based on Graph Cut algorithm[J]. Journal of Nanjing Forestry University (Natural Science Edition), 2018, 42(6): 91−98.
  • 加载中
图(7) / 表(3)
计量
  • 文章访问数:  1281
  • HTML全文浏览量:  560
  • PDF下载量:  26
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-08-30
  • 修回日期:  2019-12-03
  • 网络出版日期:  2020-07-21
  • 刊出日期:  2020-09-07

目录

    /

    返回文章
    返回