基于双目CCD测距的目标图像匹配算法研究

Research on Target Image Matching Algorithm for Binocular CCD Ranging

为了实现高精度的远距离双目CCD被动测距,提出改进的互相关匹配算法与三次曲面拟合算法,对双目CCD拍摄的两幅图像进行亚像素级匹配。介绍了双目测距系统的测距原理;进行测距图像的匹配操作,提出基于模板的灰度互相关算法,根据互相关运算的结果,提出亚像素级匹配算法,即采用三次曲面拟合方法,拟合出相关峰的亚像素级坐标;对测距实验结果进行误差分析,并修正系统误差的计算公式。实验表明,3 km以内的目标实际测量精度优于0.5%,满足高精度双目测距的精度要求。

To achieve high-precision passive ranging of binocular CCD over a long distance, two algorithms of cross-correlation matching algorithm and cubic surface fitting algorithm are put forward, to match two pictures by binocular CCD in a sub-pixel level. The ranging principle of the binocular ranging system is introduced, and the ranging images are matched and a grayscale cross-correlation algorithm is proposed based on template. According to the results of cross-correlation, the sub-pixel level matching algorithm that uses the cubic surface fitting method to fit the sub-pixel coordinates of correlation peaks is proposed. The errors of the experimental results are analyzed and the formula of calculating system errors are corrected. Experimental results show that the actual measurement accuracy of a target within 3 km is better than 0.5%, which meets the accuracy requirements of the high-precision binocular ranging.