• Laser & Optoelectronics Progress
  • Vol. 56, Issue 12, 121203 (2019)
Tingting Liu1, Peiguang Wang1、*, and Na Zhang2
Author Affiliations
  • 1 College of Electronic Information Engineering, Hebei University, Baoding, Hebei 0 71002, China
  • 2 College of Physical Science and Technology, Hebei University, Baoding, Hebei 0 71002, China
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    DOI: 10.3788/LOP56.121203 Cite this Article Set citation alerts
    Tingting Liu, Peiguang Wang, Na Zhang. Subpixel Defect Detection in Highly Reflective Workpieces Based on Zernike Moments[J]. Laser & Optoelectronics Progress, 2019, 56(12): 121203 Copy Citation Text show less
    Schematic of overall hardware device in detection system
    Fig. 1. Schematic of overall hardware device in detection system
    Overall flow chart of defect detection of workpieces
    Fig. 2. Overall flow chart of defect detection of workpieces
    Schematic of progressive image denoising algorithm based on BM3D
    Fig. 3. Schematic of progressive image denoising algorithm based on BM3D
    Schematic of image preprocessing algorithm of highly reflective workpiece
    Fig. 4. Schematic of image preprocessing algorithm of highly reflective workpiece
    Variation of edge pixels of image. (a) Original image; (b) edge pixels of local gray image; (c) 3D image
    Fig. 5. Variation of edge pixels of image. (a) Original image; (b) edge pixels of local gray image; (c) 3D image
    Subpixel edge extraction based on Zernike moment. (a) Original edge position; (b) edge position after rotation; (c) generated template image
    Fig. 6. Subpixel edge extraction based on Zernike moment. (a) Original edge position; (b) edge position after rotation; (c) generated template image
    Pixel contour lines of edge positioning error
    Fig. 7. Pixel contour lines of edge positioning error
    Experimental results. (a) Original images; (b) algorithm in Ref. [21]; (c) algorithm in Ref. [22]; (d) proposed algorithm
    Fig. 8. Experimental results. (a) Original images; (b) algorithm in Ref. [21]; (c) algorithm in Ref. [22]; (d) proposed algorithm
    Comparative experimental results under different illumination. (a) Workpiece images under different illumination; (b) results of algorithm in Ref. [21]; (c) results of algorithm in Ref. [22]; (d) results of proposed algorithm
    Fig. 9. Comparative experimental results under different illumination. (a) Workpiece images under different illumination; (b) results of algorithm in Ref. [21]; (c) results of algorithm in Ref. [22]; (d) results of proposed algorithm
    AlgorithmIn Ref. [21]In Ref. [22]Proposed
    PSNR30.2434.1842.37
    28.3331.6240.58
    30.5231.0641.28
    SSIM0.7690.8350.902
    0.7220.7850.862
    0.7340.7920.881
    Accuracy /%869296
    Table 1. Quantitative comparison of three algorithms
    Tingting Liu, Peiguang Wang, Na Zhang. Subpixel Defect Detection in Highly Reflective Workpieces Based on Zernike Moments[J]. Laser & Optoelectronics Progress, 2019, 56(12): 121203
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