摘要
针对多介质拍摄时高阶畸变折射补偿法存在的误差大、局限性强等问题,提出一种基于粒子群标定的多介质定位算法。应用Matlab软件标定工具箱得到摄像机内、外参数,在此基础上,采用粒子群优化算法标定折射平面法向量和光心到折射平面的距离,然后应用光线追踪方法,给出了一种多介质条件下的目标精确定位算法。实验结果表明,当被测物处于直立与倾斜两种位置时,应用该算法得到的相对定位误差分别为0.70%和0.45%,而应用高阶畸变折射补偿法得到的相对定位误差分别为1.71%和8.96%。该算法的相对定位误差远远低于高阶畸变折射补偿法,具有更高的定位精度,并且有效地减小了景深变化对测量精度的影响,解决了高阶畸变折射补偿法局限性强的问题。
Due to the unacceptable errors and severe limitations when using high order radial distortion coefficients to compensate refraction in multi-media imaging system, we propose the multi-media positioning algorithm based on the calibration method using particle swarm optimization （PSO）. The calibration toolbox in Matlab is employed to calculate intrinsic and external parameters of the two cameras. The normal vector and the distance from optical center to refractive interface are calibrated by using PSO algorithm. A high-precision positioning algorithm is obtained using the method of light tracing. Experimental results show that the relative positioning errors are 0.70% and 0.45 % in the proposed algorithm for uprightly and slantwise placed objects, respectively, while those are 1.71% and 8.96% in the method of high order distortion compensating refraction. Compared with the previous method, the proposed algorithm obviously decreases the influence of variation in depth of field on measurement precision and effectively improves the positioning accuracy.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2013年第5期171-176,共6页
Acta Optica Sinica
基金
国家自然科学基金(61007003)
河北省科学技术研究与发展计划(10213572)
高等学校博士学科点专项科研基金(20101333120006)资助课题
关键词
机器视觉
多介质定位
粒子群优化算法
摄像机标定
machine vision multi-media positioning particle swarm optimization algorithm camera calibration
