• DocumentCode
    3027737
  • Title

    Polysilicon Slice Dislocation Defects Segmentation and Area Statistics Based on Curve Fitting

  • Author

    Wei-hua Zhang ; Tang-you Liu

  • Author_Institution
    Coll. of Inf. Sci. & Technol., DongHua Univ., Shanghai, China
  • fYear
    2013
  • fDate
    29-30 June 2013
  • Firstpage
    925
  • Lastpage
    928
  • Abstract
    The quality of the polysilicon slice affects the efficiency of polysilicon solar cells directly, dislocation defects exist in the polysilicon generally, a large number of dislocation defects have a greater impact on efficiency of solar cells. On the basis of photoluminescence defects detection, this paper proposes a new method that progressive scan image to obtain the grayscale curve of each row, and do curve fitting for each grayscale curve to achieve defect segmentation, by comparing the segmentation results obtained by quadratic curve and Gaussian curve fitting, proves that the quadratic curve fitting can be better for defects segmentation. At last, get the proportion of defective area in total slice area. Experiments show that the method of quadratic curve fitting is efficiency and accuracy for dislocation defects segmentation and counting defects area ratio.
  • Keywords
    curve fitting; image resolution; image segmentation; inspection; photoluminescence; production engineering computing; quality control; solar cells; statistics; Gaussian curve fitting; area statistics; grayscale curve; photoluminescence defects detection; polysilicon slice dislocation defect segmentation; polysilicon solar cell quality; progressive scan image; quadratic curve fitting; Automation; Manufacturing; Area Statistics; Curve Fitting; Defect Segmentation; Dislocation Defect;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Manufacturing and Automation (ICDMA), 2013 Fourth International Conference on
  • Conference_Location
    Qingdao
  • Type

    conf

  • DOI
    10.1109/ICDMA.2013.218
  • Filename
    6598141