摘要
在层去图象法测量系统中，物体的空间坐标与截面图象坐标之间存在着复杂的非线性映射关系。如果采用完全理想条件和线性几何失真方法来标定系统，则会影响测量精度。本文提出了一种基于神经网络的标定方法，显著地提高了测量系统的精度。
In cross sectional imaging measurement system, there is complex nonlinear mapping between the object space and image space. The measurement accuracy will be low if the ideal or linear conditions are used to calibrate the system. A Calibration method based on neural network is presented in this paper. The results show a remarkable improvement of the measurement accuracy.
出处
《机械科学与技术》
CSCD
北大核心
1999年第6期985-987,共3页
Mechanical Science and Technology for Aerospace Engineering
基金
国家863 计划项目
关键词
反求工程
标定
层去图象法
神经网络
测量系统
Reverse engineering, Calibration, Cross sectional imaging, Neural network
