The state-of-art camera calibration method requires the user to provide accurate pixel coordinates of calibration plate feature points. For some cameras with special sensing range, general calibration objects’ (such as calibration plates with a centimeter-long dimension) using range is outside their clear sensing range. Using these cameras to take a picture for general calibration objects, you can only get out-of-focused blurred images that can not accurately extract feature points’ pixel coordinates. This paper analyzes the influence on the phase of the structured light based on sine grating (abbreviated as sinusoidal structured light) when optical system is in defocus state. Based on the fact that the state of focus is independent of the phase of sinusoidal structured light, a method of phase-shifted sinusoidal structured light encoding by phase shift is proposed to encode the feature points on the calibration object and this method realizes the calibration of the camera under out-of-focus condition. The experimental results show that the maximal deviation of focal length from the real value is 0.47% and the maximal pixel reprojection error is 0.17 pixels. This paper provides a solution to camera calibration with a special sensing range.
Camera calibration method based on phase encoding for out-of-focus condition
 Salvi J, Armangué X, Batlle J. A comparative review of camera calibrating methods with accuracy evaluation[J]. Pattern recognition, 2002, 35(7): 1617–1635.
 Qiu M L, Ma S D, Li Y. Overview of camera calibration for computer vision[J]. Acta Automatica Sinica, 2000, 26(1): 43–55.
邱茂林, 马颂德, 李毅. 计算机视觉中摄像机定标综述[J]. 自动化学报, 2000, 26(1): 43–55.
 Abdel-Aziz Y I, Karara H M, Hauck M. Direct linear transfor-mation from comparator coordinates into object space coordinates in close-range photogrammetry[J]. Photogrammetric Engineering & Remote Sensing, 2015, 81(2):103–107.
 Faig W. Calibration of close-range photogrammetry systems: Mathematical formulation[J]. Photogrammetric Engineering and Remote Sensing, 1975, 41(12): 1479–1486.
 Tsai R. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses[J]. IEEE Journal on Robotics and Automation, 1987, 3(4): 323–344.
 Zhang Z. A flexible new technique for camera calibration[J]. IEEE Transactions on Pattern Analysis and Machine Intelli-gence, 2000, 22(11): 1330–1334.
 Guo T, Da F P, Fang X. Camera calibration under small field of view[J]. Chinese Journal of Lasers, 2012, 39(8): 164–168
郭涛, 达飞鹏, 方旭. 小视场环境下的摄像机标定[J]. 中国激光, 2012, 39(8): 164–168.
 Wang Y W, Chen X C, Tao J Y, et al. Accurate feature detection for out-of-focus camera calibration[J]. Applied Optics, 2016, 55(28): 7964–7971.
 Szeliski R. Computer vision: algorithms and applications[M]. New York: Springer, 2010: 45–51.
 Shi A J, Bai R L, Tian Q H. 3D measurement based on struc-tured light using a combination of Gray code and line-shift patterns[J]. Opto-Electronic Engineering, 2016, 43(11): 26–32.
石爱军, 白瑞林, 田青华. Gray码结合线移的结构光三维测量[J]. 光电工程, 2016, 43(11): 26–32.
 Lin J Y, Huang J Q, Jiang K Y. Subregional Gamma pre-coding correction for phase error compensation[J]. Opto-Electronic Engineering, 2016, 43(9): 32–38 .
林俊义, 黄剑清, 江开勇. 分区域Gamma预编码校正的相位误差补偿[J]. 光电工程, 2016, 43(9): 32–38.
 Zhang W Z. Structured-light three dimensional measurement method based on digital projector[D]. Hangzhou: Zhejiang University, 2015.
张万祯. 数字投影结构光三维测量方法研究[D]. 杭州: 浙江大学, 2015.
 Li B W, Karpinsky N, Zhang S. Novel calibration method for structured-light system with an out-of-focus projector[J]. Ap-plied Optics, 2014, 53(16): 3415–3426.
Jiangsu Science and Technology Project (Industry Support) (BE2014082), Kunshan Robotics and Intelligent Equipment Technology Project (KSJ1517), and Zhejiang Research on Application of Commonweal Technology(2017C31080)
Get Citation: Yang Hao, Cai Ning, Lin Bin, et al. Camera calibration method based on phase encoding for out-of-focus condition[J]. Opto-Electronic Engineering, 2018, 45(7): 180100.