• Chinese Journal of Lasers
  • Vol. 47, Issue 12, 1204004 (2020)
Zhou Yuan1, Meng Xiangqun2, Jiang Dengbiao3, and Tang Houjun1、*
Author Affiliations
  • 1Department of Electrical Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • 2Shanghai Fangling Computer Software Co., Ltd., Shanghai 200240, China
  • 3School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, China
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    DOI: 10.3788/CJL202047.1204004 Cite this Article Set citation alerts
    Zhou Yuan, Meng Xiangqun, Jiang Dengbiao, Tang Houjun. Centerline Extraction of Structured Light Stripe Under Complex Interference[J]. Chinese Journal of Lasers, 2020, 47(12): 1204004 Copy Citation Text show less
    Laser stripe that breaks due to surface contamination of the object being measured (simulation)
    Fig. 1. Laser stripe that breaks due to surface contamination of the object being measured (simulation)
    Laser stripe disturbed by light spot (simulation)
    Fig. 2. Laser stripe disturbed by light spot (simulation)
    Laser stripe disturbed by sparks (simulation)
    Fig. 3. Laser stripe disturbed by sparks (simulation)
    Demonstration of density clustering algorithm. (a) Pixelated laser stripe image; (b) analysis of density clustering for local laser stripe image
    Fig. 4. Demonstration of density clustering algorithm. (a) Pixelated laser stripe image; (b) analysis of density clustering for local laser stripe image
    Pseudo-code of density clustering algorithm for binary image
    Fig. 5. Pseudo-code of density clustering algorithm for binary image
    Demonstration of density clustering algorithm to repair broken stripe, ε=3, P=4
    Fig. 6. Demonstration of density clustering algorithm to repair broken stripe, ε=3, P=4
    Graph data structure based on core points
    Fig. 7. Graph data structure based on core points
    Demonstration of broken stripe processing. (a) Enlarged view of simulated broken stripe interference; (b) experimental results on broken laser stripe
    Fig. 8. Demonstration of broken stripe processing. (a) Enlarged view of simulated broken stripe interference; (b) experimental results on broken laser stripe
    Experimental results of light spot interference
    Fig. 9. Experimental results of light spot interference
    Experimental results of spark interference
    Fig. 10. Experimental results of spark interference
    Enlarged view of the dotted framed area of Fig. 10
    Fig. 11. Enlarged view of the dotted framed area of Fig. 10
    Errors of different disturbed image extraction results relative to the reference centerline
    Fig. 12. Errors of different disturbed image extraction results relative to the reference centerline
    Extraction results of the proposed algorithm when applied to the actual stripe images. (a)--(d) Original images; (e)--(h) enlarged views
    Fig. 13. Extraction results of the proposed algorithm when applied to the actual stripe images. (a)--(d) Original images; (e)--(h) enlarged views
    ParameterValue
    P5
    ε8
    N200
    k3
    Table 1. Parameter setting of density clustering algorithm during experiment
    PictureWholeregionNormalregionNoisedregionNoised region(image seam)
    Fig. 10.4230.3710.8072.028
    Fig. 20.3670.3620.3991.952
    Fig. 30.3840.3620.4551.306
    Table 2. RMSE of the disturbed image extraction results relative to the reference centerlineunit:pixel
    PictureImage seamalgorithmProposedalgorithm
    Fig. 1257.136.26
    Fig. 2248.1224.30
    Fig. 3247.9425.33
    Table 3. Comparison of the average running time of different algorithmsunit:ms
    PictureImage seamalgorithmProposedalgorithm
    Fig. 13(a)123.699.03
    Fig. 13(b)126.826.13
    Fig. 13(c)120.5810.26
    Fig. 13(d)70.9020.76
    Table 4. Comparison of the average running time of different algorithms used for practical imagesunit:ms
    Zhou Yuan, Meng Xiangqun, Jiang Dengbiao, Tang Houjun. Centerline Extraction of Structured Light Stripe Under Complex Interference[J]. Chinese Journal of Lasers, 2020, 47(12): 1204004
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