• Laser & Optoelectronics Progress
  • Vol. 58, Issue 20, 2012002 (2021)
Ronghui Guo1, Yihua Zhang1, Haihua Cui1、*, Xiaosheng Cheng1, and Lanzhu Li2
Author Affiliations
  • 1College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China
  • 2Institute of Aerospace Materials and Technology, Beijing 100048, China
  • show less
    DOI: 10.3788/LOP202158.2012002 Cite this Article Set citation alerts
    Ronghui Guo, Yihua Zhang, Haihua Cui, Xiaosheng Cheng, Lanzhu Li. An Efficient Rivet Flushness Measurement Method Based on Image-to-Point-Cloud Mapping[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2012002 Copy Citation Text show less
    Flow chart of rivet flushness measurement algorithm
    Fig. 1. Flow chart of rivet flushness measurement algorithm
    Skin surface condition. (a) Image of skin surface; (b) Canny edge detection
    Fig. 2. Skin surface condition. (a) Image of skin surface; (b) Canny edge detection
    Two geometric features of contour inflection point
    Fig. 3. Two geometric features of contour inflection point
    Contour segmentation based on neighborhood features. (a)(b)(c) Original contours disturbed by noise; (d)(e)(f) neighborhood features at the inflection point of the contours
    Fig. 4. Contour segmentation based on neighborhood features. (a)(b)(c) Original contours disturbed by noise; (d)(e)(f) neighborhood features at the inflection point of the contours
    Three kinds of neighborhood features at the inflection point of the rivet contour
    Fig. 5. Three kinds of neighborhood features at the inflection point of the rivet contour
    Contour segmentation based on neighborhood features. (a)(b)(c) Contour segmentation
    Fig. 6. Contour segmentation based on neighborhood features. (a)(b)(c) Contour segmentation
    Rivet contour extraction result corresponding to the skin image shown in Fig. 2
    Fig. 7. Rivet contour extraction result corresponding to the skin image shown in Fig. 2
    Mapping relationship between camera pixel and three-dimensional point
    Fig. 8. Mapping relationship between camera pixel and three-dimensional point
    Rivet segmentation in point cloud based on image-point cloud mapping. (a) Extraction of rivet contour in image; (b) rivet segmentation in point cloud
    Fig. 9. Rivet segmentation in point cloud based on image-point cloud mapping. (a) Extraction of rivet contour in image; (b) rivet segmentation in point cloud
    Rivet segmentation in point cloud based on PCL
    Fig. 10. Rivet segmentation in point cloud based on PCL
    Measurement system for rivet flushness. (a) Hardware of measurement system; (b) software interface
    Fig. 11. Measurement system for rivet flushness. (a) Hardware of measurement system; (b) software interface
    Standard part and its measurement result. (a)Standard part; (b)measurement result of standard part
    Fig. 12. Standard part and its measurement result. (a)Standard part; (b)measurement result of standard part
    Skin part to be measured
    Fig. 13. Skin part to be measured
    Images and reconstruction results before and after introducing adaptive projection measurement method. (a)(b) Before introducing adaptive projection measurement method; (c)(d) after introducing adaptive projection measurement method
    Fig. 14. Images and reconstruction results before and after introducing adaptive projection measurement method. (a)(b) Before introducing adaptive projection measurement method; (c)(d) after introducing adaptive projection measurement method
    Rivet contour extraction and point cloud segmentation. (a) Canny edge detection result; (b) smooth contour after segmentation based on inflection point; (c) extracted rivet contour; (d) point cloud segmentation based on rivet image contour
    Fig. 15. Rivet contour extraction and point cloud segmentation. (a) Canny edge detection result; (b) smooth contour after segmentation based on inflection point; (c) extracted rivet contour; (d) point cloud segmentation based on rivet image contour
    Index12345678
    Standard value/mm0.10.20.510.10.20.51
    Measurement value/mm0.0880.1900.5200.9910.0920.1860.5280.992
    Deviation/mm0.0120.0100.0200.0090.0080.0140.0280.008
    Table 1. Measurement deviation of rivet features on standard part
    Rivet1#2#3#4#5#6#7#8#9#
    Average value/mm0.1070.1110.0910.1010.0980.0810.1270.0840.090
    Standard deviation/mm0.00480.00330.00450.00420.00430.00580.00450.00500.0037
    Table 2. Flushness measurement of rivets
    Ronghui Guo, Yihua Zhang, Haihua Cui, Xiaosheng Cheng, Lanzhu Li. An Efficient Rivet Flushness Measurement Method Based on Image-to-Point-Cloud Mapping[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2012002
    Download Citation