Trunk detection based on laser radar and vision data fusion.
Trunk detection based on laser radar and vision data fusion.
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DOI：
10.25165/ijabe.v11i6.3725
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发表时间：
2018-12
影响因子：
2.4
通讯作者：
Jinlin Xue;Bo-wen Fan;Jia-xing Yan;Dong Shuxian;Qishuo Ding
中科院分区：
文献类型：
--
作者：
Jinlin Xue;Bo-wen Fan;Jia-xing Yan;Dong Shuxian;Qishuo Ding
在林果业中，为了进行有效的生产和管理，需要对树干进行检测并获取其位置信息。提出了一种基于视觉摄像机和二维激光扫描仪数据融合的树干精确检测算法。建立了激光坐标系到图像坐标系的转换，建立了具有两个内凹区域的矩形标定板模型，实现了两个传感器数据的数据对齐。然后，分别对激光和视觉数据设计并确定感兴趣区域（ROI）的基本概率分配，通过决策层的集成，实现数据融合和基于Dempster-Shafer理论的决策。利用激光数据计算树干宽度，确定激光数据ROI的基本概率分配。提出了一种剥离式分割算法，通过计算树干状ROI的匹配度来确定视觉数据ROI的基本概率分配。一个机器人平台被用来从传感器获取数据，并执行开发的树干检测算法。通过组合标定试验，计算出激光坐标系到图像坐标系的转换矩阵，并在真实的果园进行了晴天和阴天条件下的田间试验，测量了120棵树的树干宽度，对40幅图像进行了剥离分割算法处理。实验结果表明，该算法能够成功地检测出树干，数据融合提高了树干检测能力。该算法可为果园树干检测和精确生产管理提供一种新的方法。关键词：树干检测，数据融合，证据理论，标定，激光雷达，视觉摄像机DOI：10. 25165/j.ijabe.20181106.3725引用：薛建良，范B W，严军，董世新，丁庆生.基于激光雷达与视觉数据融合的树干检测。Int J Agric & Biol Eng，2018; 11（6）：20-26.
Tree trunks detection and their location information are needed to perform effective production and management in forestry and fruit farming. A novel algorithm based on data fusion with a vision camera and a 2D laser scanner was developed to detect tree trunks accurately. The transformation was built from a laser coordinate system to an image coordinate system, and the model of a rectangle calibration plate with two inward concave regions was established to implement data alignment between two sensors data. Then, data fusion and decision with Dempster-Shafer theory were achieved through integration of decision level after designing and determining basic probability assignments of regions of interesting (RoIs) for laser and vision data respectively. Tree trunk width was calculated by using laser data to determine basic probability assignments of RoIs of laser data. And a stripping segmentation algorithm was presented to determine basic probability assignments of RoIs of vision data, by calculating the matching level of RoIs like tree trunks. A robot platform was used to acquire data from sensors and to perform the developed tree trunk detection algorithm. Combined calibration tests were conducted to calculate a conversion matrix transforming from the laser coordinate system to the image coordinate system, and then field experiments were carried out in a real pear orchard under sunny and cloudy conditions, with trunk width measurement of 120 trees and 40 images processed by the presented stripping segmentation algorithm. Results showed the algorithm was successful to detect tree trunks and data fusion improved the ability for tree trunk detection. This algorithm could provide a new method for tree trunk detection and accurate production and management in orchards. Keywords: trunk detection, data fusion, evidence theory, calibration, laser radar, vision camera DOI: 10.25165/j.ijabe.20181106.3725 Citation: Xue J L, Fan B W, Yan J, Dong S X, Ding Q S. Trunk detection based on laser radar and vision data fusion. Int J Agric & Biol Eng, 2018; 11(6): 20–26.