Study On The Key Techniques For The Plant Architecture 3D Scanner

The modeling and distribution of plant organ in growth medium, which namely plant architecture. The study of plant architecture make an important influence in the theory of growth regular, which is playing an important role in agricultural production, reasonable selection, breeding, intercropping and improve production in agricultural area. So the determination of its parameters and analysis is crucial. It's a significant issue in digital agriculture how to quantitatively analysis and research the relationship using computer simulation. With the rapid development of computer vision technology, high-precision three-dimensional information acquisition technology may fix those problems.In this paper, we realize a three-dimensional information acquisition system for plant architecture. The scanner based on the non-contact surveying is introduced, which can acquires 3D geometric information of the body surface through software processing with the body shape captured by visual equipments. The system is a high-tech product of abroad application. It can acquire automatically the coordinate information of the object surface points in 3D space, build 3D models of body surface, and save the acquired data as corresponding standard interface files. Several key problems of the scanner are emphasized:overall technical scheme of the system and camera calibration.We design and realize the 3D scanner which marked as 3DCS500. For this aim, we design the overall structure of the scanner, in which we establish hardware platform for operation stably and quickly, and we develop the system software including the user software and it's functional module. All of those are realized with VC++development tools.We research on the automatic method of calibration for the scanner. We develop the control software based on the original software, by which the camera and electric motor are controlled congruously to acquire the calibration images. Control points are detected automatically and their information are used for processing calibration parameters. With a few manual operations, a set of implicit camera parameters can be obtained.The infinite precision of calibration equipment cause abnormal error to control points, which decrease the calibration accuracy. A novel control point detection algorithm is presented to correct this error. We detect control points in the calibration images and assign world coordinates for control point by its'spatial distribution. The initial camera parameters are calculated with the original information of control points using the Levenberg-Marquardt algorithm. Then the pixel distance between control point and it's project is compared with the overall RMS error, by which we adjust the image coordinates of control point. The adjusted control points are utilized to compute a new parameters and the comparison is processed again until convergence. This method can improve calibration accuracy with a small time consuming.There are always exist deviation in assemble of planar object, which cause errors in calibration.We introduce two calibration correction methods to correct this deviation. In the first methos, we take an reference image which is the image of plumb line. With the reference image the correct points are abtained. Using the correct points we calculate the skew-correction coefficient matrix in the skew model, by which the error of information of the control point is corrected. In the second method, we produce a calibration correction method based on the information feature of control points. A skew correction model of the planar object is established to amend the skew bias. We find out and prove that the skew bias of the control point which is close to the fix point is micro enough to be ignored. Based on this property, the optimization algorithm is developed to estimate the skew factors quickly and steadily. The improved accuracy of information of control points improves calibration and the implicit camera parameters can be provided, which considerably benefits 3D reconstruction.The calibration equipments are expensive. So we develop a novel calibration system for the plant 3D scanner. With a few manual operations, a set of implicit camera parameters can be estimated directly using this system. Control points are detected with the refinement algorithm developed by us and numbered. The information of control points are devoted into the camera model and the camera parameters can be estimated. Many experiments denote the feasibility and the accuracy of the proposed method. Comparing with manual calibration methods, this system can satisfy the demand of the plant 3D scanner, which is convenient and dependable.