Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 879675, 12 pages
http://dx.doi.org/10.1155/2015/879675
Research Article

Automatic Finger Interruption Detection in Electroluminescence Images of Multicrystalline Solar Cells

1Department of Computer Science and Information Engineering, National Central University, No. 300, Jhongda Road, Jhongli 32001, Taiwan
2Department of Electronic Engineering, Chien Hsin University of Science and Technology, No. 229, Jianxing Road, Jhongli 32097, Taiwan

Received 12 December 2014; Accepted 11 February 2015

Academic Editor: Mo Li

Copyright © 2015 Din-Chang Tseng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. C. Sener and V. Fthenakis, “Energy policy and financing options to achieve solar energy grid penetration targets: accounting for external costs,” Renewable and Sustainable Energy Reviews, vol. 32, pp. 854–868, 2014. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Abdelhamid, R. Singh, and M. Omar, “Review of microcrack detection techniques for silicon solar cells,” IEEE Journal of Photovoltaics, vol. 4, no. 1, pp. 514–524, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. P. Chaturvedi, B. Hoex, and T. M. Walsh, “Broken metal fingers in silicon wafer solar cells and PV modules,” Solar Energy Materials and Solar Cells, vol. 108, pp. 78–81, 2013. View at Publisher · View at Google Scholar · View at Scopus
  4. R. De Rose, A. Malomo, P. Magnone et al., “A methodology to account for the finger interruptions in solar cell performance,” Microelectronics Reliability, vol. 52, no. 9-10, pp. 2500–2503, 2012. View at Publisher · View at Google Scholar · View at Scopus
  5. T. Fuyuki and A. Kitiyanan, “Photographic diagnosis of crystalline silicon solar cells utilizing electroluminescence,” Applied Physics A: Materials Science and Processing, vol. 96, no. 1, pp. 189–196, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. D.-M. Tsai, S.-C. Wu, and W.-C. Li, “Defect detection of solar cells in electroluminescence images using Fourier image reconstruction,” Solar Energy Materials and Solar Cells, vol. 99, pp. 250–262, 2012. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Israil, S. A. Anwar, and M. Z. Abdullah, “Automatic detection of micro-crack in solar wafers and cells: a review,” Transactions of the Institute of Measurement and Control, vol. 35, no. 5, pp. 606–618, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. Z. Wang, F. Yang, G. Pan, J. Gao, and H. Zhang, “Research on detection technology for solar cells multi-defects in complicated background,” Journal of Information and Computational Science, vol. 11, no. 2, pp. 449–459, 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. D.-M. Tsai, S.-C. Wu, and W.-Y. Chiu, “Defect detection in solar modules using ICA basis images,” IEEE Transactions on Industrial Informatics, vol. 9, no. 1, pp. 122–131, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. M. Filippone, F. Camastra, F. Masulli, and S. Rovetta, “A survey of kernel and spectral methods for clustering,” Pattern Recognition, vol. 41, no. 1, pp. 176–190, 2008. View at Publisher · View at Google Scholar · View at Scopus
  11. J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 888–905, 2000. View at Publisher · View at Google Scholar · View at Scopus
  12. W.-Y. Chen, Y. Song, H. Bai, C.-J. Lin, and E. Y. Chang, “Parallel spectral clustering in distributed systems,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 3, pp. 568–586, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. U. von Luxburg, “A tutorial on spectral clustering,” Statistics and Computing, vol. 17, no. 4, pp. 395–416, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  14. L. J. O'Donnell and C.-F. Westin, “Automatic tractography segmentation using a high-dimensional white matter atlas,” IEEE Transactions on Medical Imaging, vol. 26, no. 11, pp. 1562–1575, 2007. View at Publisher · View at Google Scholar · View at Scopus