• Frontiers of Optoelectronics
  • Vol. 10, Issue 2, 151 (2017)
Yu HAN, Yubin WU, Danhua CAO*, and Peng YUN
Author Affiliations
  • School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
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    DOI: 10.1007/s12200-017-0687-7 Cite this Article
    Yu HAN, Yubin WU, Danhua CAO, Peng YUN. Defect detection on button surfaces with the weighted least-squares model[J]. Frontiers of Optoelectronics, 2017, 10(2): 151 Copy Citation Text show less
    References

    [1] Li W B, Lu C H, Zhang J C. A lower envelope Weber contrast detection algorithm for steel bar surface pit defects. Optics & Laser Technology, 2013, 45(1): 654-659

    [2] Crispin A J, Rankov V. Automated inspection of PCB components using a genetic algorithm template-matching approach. International Journal of Advanced Manufacturing Technology, 2007, 35(3): 293- 300

    [3] Arivazhagan S, Ganesan L, Bama S. Fault segmentation in fabric images using Gabor wavelet transform. Machine Vision and Applications, 2006, 16(6): 356-363

    [4] Li W C, Tsai D M. Wavelet-based defect detection in solar wafer images with inhomogeneous texture. Pattern Recognition, 2012, 45 (2): 742-756

    [5] Tsai D M, Wu S C, Chiu W Y. Defect detection in solar modules using ICA basis images. IEEE Transactions on Industrial Informatics, 2013, 9(1): 122-131

    [6] Cen Y G, Zhao R Z, Cen L H, Cui L H, Miao Z J, Wei Z. Defect inspection for TFT-LCD images based on the low-rank matrix reconstruction. Neurocomputing, 2015, 149: 1206-1215

    [7] Zhou W, Fei M, Zhou H, Li K. A sparse representation based fast detection method for surface defect detection of bottle caps. Neurocomputing, 2014, 123: 406-414

    [8] Bai X, Fang Y, Lin W, Wang L, Ju B F. Saliency-based defect detection in industrial images by using phase spectrum. IEEE Transactions on Industrial Informatics, 2014, 10(4): 2135-2145

    [9] sai D M, Chiang I Y, Tsai Y H. A shift-tolerant dissimilarity measure for surface defect detection. IEEE Transactions on Industrial Informatics, 2012, 8(1): 128-137

    [10] Chan C H, Pang G K. Fabric defect detection by Fourier analysis. IEEE Transactions on Industry Applications, 2000, 36(5): 1267- 1276

    [11] Ngan H Y T, Pang G K H, Yung S P, Ng M K. Wavelet based methods on patterned fabric defect detection. Pattern Recognition, 2005, 38(4): 559-576

    [12] Yang X, Pang G, Yung N. Robust fabric defect detection and classification using multiple adaptive wavelets. IEE Proceedings -Vision Image and Signal Processing, 2005, 152(6): 715

    [13] Ralló M, Millán M S, Escofet J. Unsupervised novelty detection using Gabor filters for defect segmentation in textures. Journal of the Optical Society of America A, Optics, Image Science, and Vision, 2009, 26(9): 1967-1976

    [14] Kumar A, Pang G K. Defect detection in textured materials using Gabor filters. IEEE Transactions on Industry Applications, 2002, 38 (2): 425-440

    [15] Wang C C, Jiang B C, Lin J Y, Chu C C. Machine vision-based defect detection in IC images using the partial information correlation coefficient. IEEE Transactions on Semiconductor Manufacturing, 2013, 26(3): 378-384

    [16] Zontak M, Cohen I. Defect detection in patterned wafers using anisotropic kernels. Machine Vision and Applications, 2010, 21(2): 129-141

    [17] Stauffer C, Grimson W E L. Adaptive background mixture models for real-time tracking. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1999, 2: 246-252

    [18] Kaewtrakulpong P, Bowden R. An improved adaptive background mixture model for real-time tracking with shadow detection. Springer US, 2002: 135-144

    [19] Zivkovic Z. Improved adaptive Gaussian mixture model for background subtraction. In: Proceedings of International Conference on Pattern Recognition, 2004

    Yu HAN, Yubin WU, Danhua CAO, Peng YUN. Defect detection on button surfaces with the weighted least-squares model[J]. Frontiers of Optoelectronics, 2017, 10(2): 151
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