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. doi: 10.12086/oee.2018.180100
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. doi: 10.12086/oee.2018.180100

Camera calibration method based on phase encoding for out-of-focus condition

    Fund Project: Supported by 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)
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  • 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.
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  • Overview: With development in the past decades, the normal camera calibration method has become more and more mature. Among them, the method proposed by Zhang is a representative one. However, there is still a lack of the calibration method of some cameras and lenses used in special occasions. Recently, there are a few calibration studies for cameras with special imaging ranges, such as macro cameras and telephoto cameras. In 2012, Guo proposed a method for macro camera calibration using a semicircle template instead of a checkerboard in the general method. This method needs to fit the semicircle curve during the actual use. This step is difficult in the use of this method. Wang proposed a calibration pattern that can still be detected when the camera is out of focus, but its rendering method is difficult.

    Our works are as follows: The state-of-art camera calibration method requires the user to provide accurate pixel coordinate 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. This paper analyzes the influence of the focusing state of the camera imaging system on the optical phase information of a sinusoidal structured light. Using the properties that the sinusoidal structured light's phase information is independent of the focusing state of the camera, this paper proposes a method for encoding a normal calibration object using sinusoidal structured light to make the calibration of the camera in the defocus state make true. This method uses an in-focus camera to get the phase information of the encoded normal calibration object. The out-of-focus camera uses the phase information to calculate the feature points' accurate coordinates by the phase information. Then, the traditional method (e.g. Zhang method) is used to calculate the intrinsic, extrinsic parameters and distortion coefficient of the out-of-focus camera. Based on this method, the camera parameters can be accurately calibrated by using a blurred picture of the coded calibration object. This paper provides a cheap and convenient solution to the calibration of these special cameras. We don't have to manufacture the special calibration objects. The experiment results show that this method can calibrate special camera parameters accurately under different defocus state. After experimental verification, the calibrated focal length deviation from the real value is 0.47%, the average pixel reprojection error is 0.17 pixels.

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