结构光三维视觉检测系统的标定方法研究

提出了一种新的结构光三维视觉检测系统的标定方法,将BP神经网络和线性标定方法结合起来,用线性标定方法标定结构光系统的线性部分,用BP神经网络来描述该结构光系统的其他部分.结果表明:该方法结合了神经网络和线性标定方法的优点,不仅给出了结构光三维检测系统中CCD相机的内部和外部参数,而且利用神经网络的非线性逼近能力,补偿由于镜头径向畸变、切向畸变等因素引起的系统非线性误差,并且精度高、抗噪声能力强及鲁棒性好.

A Calibration Method for Structured Light 3-D Vision Systems

Traditional method often need complicated mathematical model,and the neural network method can't tell the perspective-projection-transformation matrix between the world 3-D points and the corresponding 2-D image pixels.A new calibration method for structured light system is propoed in this paper,which using the BP neural network and the linear calibration method and utilize the multilayer feed-forward neural network to compensate the nonlinear error of structured light system brought by lens distortion,etc.The experiments results show that the method we proposed is feasible,effective,and has high anti-noise ability.