可变阶数NURBS曲面的相机标定模型

Variable Order NURBS Surface Model for Camera Calibration

农用机器人对作业对象的定位、测量和识别等都需要借助视觉系统(相机)来完成,因此相机标定精度至关重要。提出一种可变阶数NURBS曲面的相机标定模型,即在像平面的高失真区域应用较高阶数的NURBS曲面模型作为标定依据,其他区域用较低阶数的NURBS曲面模型,在不过多增加标定计算负担的前提下,提高了整体的标定精度。该模型应用标定误差的预评估方法将像平面进行“区块”划分,依此匹配模型阶数,实现标定精度和计算量的综合优化。由于NURBS曲面隐式标定模型的优越性能,使标定不依赖于相机的光学特性,理论上可校正相机的所有失真。实验结果表明,标定平均误差在0.89 mm以内,可满足农用机器人的应用要求。

For an agricultural robot,camera vision implements the function of detecting ripeness,shape,size of crops and locating the stems precisely in order to harvest with no damage.A common calibration model with adjustable accuracy was needed to achieve higher precision in cooperative works of certain manipulator and CCD cameras.Creatively,a variable order NURBS surface model for camera calibration was presented.Firstly,seven images were acquired by a slide way and a calibration board of A0 size.The data was extracted afterward.Based on the thought of NPBS method,four double NURBS surface calibration models with order of 3,4,5 and 6 were setup respectively using data of five images(index:1,3,4,5 and 7).Other two images(index:2 and 6)were used to evaluate the calibration error.According to the requiring preciseness and the calculating time,the models of order 3 and 4 were chosen to accomplish model switching(higher order models can be chosen according to higher precision requirement).Secondly,camera image plane was subdivided evenly with respect to parameter(u,v).In each subdivision,an arithmetic average deviation of calibration was calculated by using the model with lower order.Then a threshold was determined,and the diagram of model switching was formed.That meant using a higher order NURBS surface model in the higher distortion region,vice versa.Thus,orders of the NURBS surface model can be chosen according to subdivision of the image plane based on pre-evaluation of the calibration error.In experiments,it was proved that the average calibration error was under 0.89 mm.It was accurate enough for our agricultural robot prototype.