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Active Contour Method Based Sub-pixel Critical Dimension Measurement of Thin Film Transistor Liquid Crystal Display (TFT-LCD) Patterns

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Abstract

A novel application-oriented sub-pixel measurement method utilizing an active contour model with image resampling is presented for a critical dimension (CD) measurement of pixel patterns of a flat-panel thin film transistor crystal display (TFT-LCD) and organic light-emitting diode display. In modern manufacturing of flat panel display, optical measurement of each dimension of pixel patterns has a critical role in the process control, and the resolution of a measurement system becomes a limitation of the manufacturing process. Several methods have been developed to overcome this limit at the image post processing stage, but as the level of pixel integration and manufacturing throughput are increasing rapidly, more robust and effective inspection approach is required. In this paper, a novel sub-pixel level edge detection algorithm with active contour method and fast pixel resampling is proposed for micron scale CD measurement, and its advantages on measurement repeatability and noise handling are presented, along with the results of various industrial sample measurements and comparison with conventional critical dimension measurement algorithms.

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References

  1. Lee, J. Y., Kim, T. W., & Pahk, H. J. (2017). Robust defect detection method for a non-periodic TFT-LCD pad area. International Journal of Precision Engineering and Manufacturing,18(8), 1093–1102.

    Article  Google Scholar 

  2. Kim, M.-G. (2019). Improved measurement of thin film thickness in spectroscopic reflectometer using convolutional neural networks. International Journal of Precision Engineering and Manufacturing. https://doi.org/10.1007/s12541-019-00260-4.

    Article  Google Scholar 

  3. Park, J., Kim, J. A., Ahn, H., Bae, J., & Jin, J. (2019). A review of thickness measurements of thick transparent layers using optical interferometry. International Journal of Precision Engineering and Manufacturing,20(3), 463–477.

    Article  Google Scholar 

  4. Lee, J. H., Kim, Y. S., Kim, S. R., Lee, I. H., & Pahk, H. J. (2008). Real-time application of critical dimension measurement of TFT-LCD pattern using a newly proposed 2D image-processing algorithm. Optics and Lasers in Engineering,46(7), 558–569.

    Article  Google Scholar 

  5. Breder, R. L. B., Estrela, V. V., & de Assis, J. T. (2009). Sub-pixel accuracy edge fitting by means of b-spline. In 2009 IEEE international workshop on multimedia signal processing (pp. 1–5). IEEE.

  6. Park, S. H., Kim, T. W., Lee, J. H., & Pahk, H. J. (2014). Real-time critical dimension measurement of thin film transistor liquid crystal display patterns using optical coherence tomography. Journal of Electronic Imaging,23(1), 013001.

    Article  Google Scholar 

  7. Doan, N. T., Moon, J. H., Kim, T. W., & Pahk, H. J. (2012). A fast image enhancement technique using a new scanning path for critical dimension measurement of glass panels. International Journal of Precision Engineering and Manufacturing,13(12), 2109–2114.

    Article  Google Scholar 

  8. Dodgson, N. A. (1997). Quadratic interpolation for image resampling. IEEE Trans.,6, 1322–1326.

    Google Scholar 

  9. Hou, H. S., & Andrews, H. C. (1978). Cubic splines for image interpolation and digital filtering. IEEE Transactions on Acoustics, Speech, and Signal Processing,ASSP-26, 508–517.

    MATH  Google Scholar 

  10. Keys, R. G. (1981). Cubic convolution interpolation for digital image processing. IEEE Transactions on Acoustics, Speech, and Signal Processing,ASSP-29, 1153–1160.

    Article  MathSciNet  Google Scholar 

  11. Unser, M. (1999). Splines: A perfect fit for signal and image processing. IEEE Signal Processing Magazine,16, 22–38.

    Article  Google Scholar 

  12. Kisworo, M., Venkatesh, S., & West, G. (1991). 2-D edge feature extraction to subpixel accuracy using the generalized energy approach. In TENCON’91. Region 10 international conference on EC3-energy, computer, communication and control systems (Vol. 3, pp. 344–348). IEEE.

  13. Vandewalle, P., Süsstrunk, S., & Vetterli, M. (2006). A frequency domain approach to registration of aliased images with application to super-resolution. EURASIP Journal on Advances in Signal Processing,2006(1), 071459.

    Article  Google Scholar 

  14. Zweig, G. (2003). Super-resolution Fourier transforms by optimisation, and ISAR imaging. IEE Proceedings-Radar, Sonar and Navigation,150(4), 247–252.

    Article  Google Scholar 

  15. Anbarjafari, G., & Demirel, H. (2010). Image super resolution based on interpolation of wavelet domain high frequency subbands and the spatial domain input image. ETRI Journal,32(3), 390–394.

    Article  Google Scholar 

  16. Doan, N. T., Moon, J. H., Kim, T. W., & Pahk, H. J. (2012). Novel, fast, edge-directed image reconstruction algorithm using a substepping system for critical-dimension measurement of glass panels. Journal of Electronic Imaging,21(3), 033028.

    Article  Google Scholar 

  17. Burger, W., & Burge, M. J. (2009). Principles of digital image processing: Core algorithms. London: Springer.

    Book  Google Scholar 

  18. Kass, M., Witkin, A., & Terzopoulos, D. (1988). Snakes: Active contour models. International Journal of Computer Vision,1(4), 321–331.

    Article  Google Scholar 

  19. Cohen, L. D. (1991). On active contour models and balloons. CVGIP: Image Understanding,53(2), 211–218.

    Article  Google Scholar 

  20. Xu, C., & Prince, J. L. (1998). Snakes, shapes, and gradient vector flow. IEEE Transactions on Image Processing,7(3), 359–369.

    Article  MathSciNet  Google Scholar 

  21. Sonka, M., Hlavac, V., & Boyle R. (1998). Image processing: Analysis and machine vision (2nd Edn.). Cengage Learning. ISBN-13: 978-0534953935.

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Author notes

  1. Jeong Hoon Lee and Tai-Wook Kim have contributed equally to this work.

Authors and Affiliations

  1. School of Mechanical Engineering, Seoul National University, 1, Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea

    Jeong Hoon Lee, Dong Hun Ku & Heui Jae Pahk

  2. Department of Mechatronics, Daelim University College, 29, Imgok-ro, Dongan-gu, Anyang-si, Gyeonggi-do, 13916, South Korea

    Tai-Wook Kim

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  1. Jeong Hoon Lee
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  4. Heui Jae Pahk
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Correspondence to Tai-Wook Kim.

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Lee, J.H., Kim, TW., Ku, D.H. et al. Active Contour Method Based Sub-pixel Critical Dimension Measurement of Thin Film Transistor Liquid Crystal Display (TFT-LCD) Patterns. Int. J. Precis. Eng. Manuf. 21, 831–841 (2020). https://doi.org/10.1007/s12541-019-00314-7

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