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J. Imaging 2016, 2(4), 28; doi:10.3390/jimaging2040028

3D Reconstruction of Plant/Tree Canopy Using Monocular and Binocular Vision

Department of Agricultural & Biological Engineering, University of Florida, Gainesville, FL 32611, USA
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Author to whom correspondence should be addressed.
Academic Editors: Gonzalo Pajares Martinsanz and Francisco Rovira-Más
Received: 29 August 2016 / Revised: 16 September 2016 / Accepted: 19 September 2016 / Published: 29 September 2016
(This article belongs to the Special Issue Image Processing in Agriculture and Forestry)
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Abstract

Three-dimensional (3D) reconstruction of a tree canopy is an important step in order to measure canopy geometry, such as height, width, volume, and leaf cover area. In this research, binocular stereo vision was used to recover the 3D information of the canopy. Multiple images were taken from different views around the target. The Structure-from-motion (SfM) method was employed to recover the camera calibration matrix for each image, and the corresponding 3D coordinates of the feature points were calculated and used to recover the camera calibration matrix. Through this method, a sparse projective reconstruction of the target was realized. Subsequently, a ball pivoting algorithm was used to do surface modeling to realize dense reconstruction. Finally, this dense reconstruction was transformed to metric reconstruction through ground truth points which were obtained from camera calibration of binocular stereo cameras. Four experiments were completed, one for a known geometric box, and the other three were: a croton plant with big leaves and salient features, a jalapeno pepper plant with median leaves, and a lemon tree with small leaves. A whole-view reconstruction of each target was realized. The comparison of the reconstructed box’s size with the real box’s size shows that the 3D reconstruction is in metric reconstruction. View Full-Text
Keywords: 3D images; multiple view reconstruction; metric reconstruction; plant reconstruction; machine vision; stereo vision 3D images; multiple view reconstruction; metric reconstruction; plant reconstruction; machine vision; stereo vision
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ni, Z.; Burks, T.F.; Lee, W.S. 3D Reconstruction of Plant/Tree Canopy Using Monocular and Binocular Vision. J. Imaging 2016, 2, 28.

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