摘要
对空间圆几何参数的非接触在线测量方法进行了研究。通过在区域划分中引入模糊化思想,基于模糊隶属度构建一种神经网络的拓扑结构,采用立体标靶进行摄像机标定。面向局部检测区域小的空间尺寸测量问题,利用图像的梯度相关作为匹配特性,开发一种高效的基于梯度图像的立体匹配算法。在实验研究中,对某车身翼子板安装孔进行了检测,结果显示当空间圆所在平面与图像平面约50°角时,测量空间圆的相对误差优于±0.6%。研究结果表明,提出的方法测量精度高,并适用于在线测量。
The non-contact inspection method for the geometrical parameters of spatial circle is studied.A neural network topology is constructed based on fuzzy membership degree through introducing fuzzy theory at the regional division.The three-dimensional target is used for camera calibration.A gradient-based stereo image matching algorithm is developed by using the image gradient-related as the matching feature,especially for the space size measurement of a small region.Experimental results show that the relative error of spatial circle measurement is better than ±0.6% by the proposed approach,when the space plane containing spatial circle and the image plane is at 50°.This indicates that the proposed approach can achieve a high precision.It is applied to on-line measurement.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第32期55-58,62,共5页
Computer Engineering and Applications
基金
国家重点实验室基金资助项目(No.KLVBDM2005003)
吉林省科技发展计划基金资助项目(No.20080539)
关键词
模糊神经网络
摄像机标定
空间圆
几何参数
双目立体视觉
fuzzy neural network； camera calibration； spatial circle； geometric parameters； binocular stereo vision；
