Volume 49 Issue 1
Jan.  2020
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Song Xiaofeng, Li Jupeng, Chen Houjin, Li Feng, Wan Chengkai. Laser centerline extraction method for 3D measurement of structured light in multi-scenarios[J]. Infrared and Laser Engineering, 2020, 49(1): 0113004-0113004(8). doi: 10.3788/IRLA202049.0113004
Citation: Song Xiaofeng, Li Jupeng, Chen Houjin, Li Feng, Wan Chengkai. Laser centerline extraction method for 3D measurement of structured light in multi-scenarios[J]. Infrared and Laser Engineering, 2020, 49(1): 0113004-0113004(8). doi: 10.3788/IRLA202049.0113004

Laser centerline extraction method for 3D measurement of structured light in multi-scenarios

doi: 10.3788/IRLA202049.0113004
  • Received Date: 2019-10-05
  • Rev Recd Date: 2019-11-15
  • Publish Date: 2020-01-28
  • 3D measurement of structured light technology is an extremely vital approach to obtain 3D information of objects. Extraction of the centerline of laser stripe is a key factor that could affect the accuracy and speed of 3D measurement of structured light in the meantime. A method of extracting centerline of laser stripe for 3D measurement of structured light that adaptive to multiple scenarios was proposed. The adaptive convolution template was generated by making full use of the geometric information and correlation of laser stripe in the image, which can filter and enhance the image quality of laser stripe and enable the gray value of cross-section of laser stripe satisfy the Gauss distribution. The sub-pixel accurate localization and extraction of laser stripe centerline were realized by gray weighted algorithm. The experimental results show that the proposed adaptive convolutional algorithm can extract the laser stripe centerlines of the objects with different shapes and materials based on multi-scenarios and overcome the influence of uneven brightness and noise at the same time. Based on the algorithm, the extraction time of single frame is shortened to 0.107 s and the relative error is reduced to 0.076 5%, which improves the extraction accuracy and speed of laser stripe centerline effectively.
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    [2] Li Qi, Zhang Yixin, Zhang Xuping, et al. Statistical behavior analysis and precision optimization for the laser stripe center detector based on Steger's algorithm[J]. Optics Express, 2013, 21(11):13442-13449.
    [3] Chang Yaceng, Chen Jing, Tian Junwei. Sub-pixel edge detection algorithm based on Gauss fitting[J]. Journal of Computer Applications, 2011, 31(1):179-181. (in Chinese)
    [4] Yang Yongming, Wang Zhenzhou. An efficient and robust stripe extraction method for structured light measurement system[C]//Proceedings of the International Conference on Advances in Image Processing. Bangkok, Thailand-August 25-27, 2017:103-107.
    [5] Sun Panqing, Yang Yongyue, Liangliang He. An improved Gaussian fitting method used in light-trap center acquiring[J]. Electronic Design Engineering, 2012, 20(13):179-185. (in Chinese)
    [6] Li Yuehua, Zhou Jingbo, Huang Fengshan. Sub-pixel extraction of laser stripe center using an improved gray-gravity method[J]. Sensors, 2017, 17(4):1-13.
    [7] Wang Zehao, Zhang Zhongwei. Adaptive direction template method to extract the center of structured light[J]. Laser Journal, 2017, 38(1):60-64. (in Chinese)
    [8] Yin Xiaoqin, Tao Wei, Feng Yiyang, et al. Laser stripe extraction method in dustrial enviroments utilizing self-adaptive convolution technique[J]. Applied Optics, 2017, 56(10):2653-2660.
    [9] Jin Jun, Li Dehua, Li Heping. New method for obtaining the center of structured light stripe[J]. Computer Engineering and Applications, 2006, 42(4):42-44. (in Chinese)
    [10] Fisher R B, Naidu D K. A Comparison of Algorithms for Subpixel Peak Detection[M]. Berlin Heidelberg:Springer Press, 1996:285-404.
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Laser centerline extraction method for 3D measurement of structured light in multi-scenarios

doi: 10.3788/IRLA202049.0113004
  • 1. School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China;
  • 2. Beijing Century Real Technology Co., Ltd., Beijing 100085, China

Abstract: 3D measurement of structured light technology is an extremely vital approach to obtain 3D information of objects. Extraction of the centerline of laser stripe is a key factor that could affect the accuracy and speed of 3D measurement of structured light in the meantime. A method of extracting centerline of laser stripe for 3D measurement of structured light that adaptive to multiple scenarios was proposed. The adaptive convolution template was generated by making full use of the geometric information and correlation of laser stripe in the image, which can filter and enhance the image quality of laser stripe and enable the gray value of cross-section of laser stripe satisfy the Gauss distribution. The sub-pixel accurate localization and extraction of laser stripe centerline were realized by gray weighted algorithm. The experimental results show that the proposed adaptive convolutional algorithm can extract the laser stripe centerlines of the objects with different shapes and materials based on multi-scenarios and overcome the influence of uneven brightness and noise at the same time. Based on the algorithm, the extraction time of single frame is shortened to 0.107 s and the relative error is reduced to 0.076 5%, which improves the extraction accuracy and speed of laser stripe centerline effectively.

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