Volume 47 Issue 6
Jul.  2018
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Zou Yuanyuan, Li Pengfei, Zuo Kezhu. Field calibration method for three-line structured light vision sensor[J]. Infrared and Laser Engineering, 2018, 47(6): 617002-0617002(6). doi: 10.3788/IRLA201847.0617002
Citation: Zou Yuanyuan, Li Pengfei, Zuo Kezhu. Field calibration method for three-line structured light vision sensor[J]. Infrared and Laser Engineering, 2018, 47(6): 617002-0617002(6). doi: 10.3788/IRLA201847.0617002

Field calibration method for three-line structured light vision sensor

doi: 10.3788/IRLA201847.0617002
  • Received Date: 2018-01-05
  • Rev Recd Date: 2018-02-15
  • Publish Date: 2018-06-25
  • The three-line structured light vision sensor is widely used in industrial field measurement due to it has many advantages such as speedy and abundant information. In order to calibrate the three-line structured light vision sensor on-field with high accuracy and high efficiency, a new calibration method based on support vector machine was proposed. Firstly, a calibration target was designed. Secondly, calibration images were captured and feature points were identified. And then sub-pixel coordinates of feature points were extracted. Thirdly, a direct mapping model according to image coordinates and three dimension coordinates of feature points was built based on support vector machine. Finally, image coordinates of the calibration points were put into the model and their three dimension coordinates could be obtained. So the three-line structured light vision sensor could be calibrated directly. Experimental results demonstrated that this direct calibration method had high accuracy; its mean absolute error was 0.021 1 mm in Y direction and 0.015 0 mm in Z direction. It concludes that this method is easy, fast and suitable for field calibration.
  • [1] Xie Zexiao, Chen Wenzhu, Chi Shukai, et al. Industrial robot positioning system based on the guidance of the structured-light vision[J]. Acta Optica Sinica, 2016, 36(10):1015001. (in Chinese)
    [2] Konov S G, Khokholikov A A, Gololobova A A. The use of structured light for a photogrammetric method of measuring surfaces having complex shape[J]. Measurement Techniques, 2015, 58(7):757-759.
    [3] Wang Li, Li Guangjun, Yang Xinyong, et al. One-site calibration of mounted parameter method for 3D mobile laser scanning[J]. Infrared and Laser Engineering, 2016, 45(11):1106005. (in Chinese)
    [4] Sung K, Lee H, Choi Y S, et al. Development of a multiline laser vision sensor for joint tracking in welding[J]. Weld Journal, 2009, 88(4):79-85.
    [5] Wang Zongyi, Li Hongwei, Li Dianpu, et al. A direct calibration method for structured light[C]//IEEE International Conference on Mechatronics and Automation, 2005:1283-1287.
    [6] Kuang Yongcong, Cui Liangchun. A new calibration method for line-structured light vision sensor based on linear scale[J]. Journal of South China University of Technology, 2016, 44(1):71-77. (in Chinese)
    [7] Trucco E, Fisher R B. Acquisition of consistent range data using local calibration[C]//IEEE International Conference on Robotics and Automation, 1994:3410-3415.
    [8] Zhang Guangjun, Wei Zhenzhong. A method of structured light based 3D vision inspection using BP neural network[J]. Chinese Journal of Scientific Instrument, 2002, 23(1):31-35. (in Chinese)
    [9] Dipanda A, Woo S, Marzani F, et al. 3D shape reconstruction in an active stereo vision system using genetic algorithms[J]. Pattern Recognition, 2003, 36(9):2143-2159.
    [10] Abhisek U. Support vector machine[J]. Computer Science, 2007, 1(3):1303-1308.
    [11] Awad M, Khanna R. Support vector regression[J]. Neural Information Processing Letters Reviews, 2007, 11(10):203-224.
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Field calibration method for three-line structured light vision sensor

doi: 10.3788/IRLA201847.0617002
  • 1. School of Mechanical Engineering,Shenyang Jianzhu University,Shenyang 110168,China;
  • 2. National-Local Joint Engineering Laboratory of NC Machining Equipment and Technology of High-Grade Stone,Shenyang 110168,China

Abstract: The three-line structured light vision sensor is widely used in industrial field measurement due to it has many advantages such as speedy and abundant information. In order to calibrate the three-line structured light vision sensor on-field with high accuracy and high efficiency, a new calibration method based on support vector machine was proposed. Firstly, a calibration target was designed. Secondly, calibration images were captured and feature points were identified. And then sub-pixel coordinates of feature points were extracted. Thirdly, a direct mapping model according to image coordinates and three dimension coordinates of feature points was built based on support vector machine. Finally, image coordinates of the calibration points were put into the model and their three dimension coordinates could be obtained. So the three-line structured light vision sensor could be calibrated directly. Experimental results demonstrated that this direct calibration method had high accuracy; its mean absolute error was 0.021 1 mm in Y direction and 0.015 0 mm in Z direction. It concludes that this method is easy, fast and suitable for field calibration.

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