KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

Implementation of a High-speed Template Matching System for Wafer-vision Alignment Using FPGA

  • Jae-Hyuk So (Data Convergence Platform Research Center, Korea Electronics Technology Institute) ;
  • Minjoon Kim (Division of Semiconductor and Electronics Engineering, Hankuk University of Foreign Studies)
  • Received : 2024.03.28
  • Accepted : 2024.06.03
  • Published : 2024.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

In this study, a high-speed template matching system is proposed for wafer-vision alignment. The proposed system is designed to rapidly locate markers in semiconductor equipment used for wafer-vision alignment. We optimized and implemented a template-matching algorithm for the high-speed processing of high-resolution wafer images. Owing to the simplicity of wafer markers, we removed unnecessary components in the algorithm and designed the system using a field-programmable gate array (FPGA) to implement high-speed processing. The hardware blocks were designed using the Xilinx ZCU104 board, and the pyramid and matching blocks were designed using programmable logic for accelerated operations. To validate the proposed system, we established a verification environment using stage equipment commonly used in industrial settings and reference-software-based validation frameworks. The output results from the FPGA were transmitted to the wafer-alignment controller for system verification. The proposed system reduced the data-processing time by approximately 30% and achieved a level of accuracy in detecting wafer markers that was comparable to that achieved by reference software, with minimal deviation. This system can be used to increase precision and productivity during semiconductor manufacturing processes.

Keywords

Acknowledgement

This work was supported by the Technology Innovation Program (20015975, Development of an apparatus for probe head based on High Precision 3 Axis Loader) funded By the Ministry of Trade, Industry & Energy(MOTIE, Korea). This work was also supported by Hankuk University of Foreign Studies Research Fund of 2024.

References

  1. J. KIM, "New Wafer Alignment Process Using Multiple Vision Method for Industrial Manufacturing," Electronics, vol.7, no.3, 2018.
  2. M. Cong, X. Kong, Y. Du, J. Liu, "Wafer Pre-Aligner System Based on Vision Information Processing," Information Technology Journal, vol.6, no.8, pp.1245-1251, 2007.
  3. C. Chen, C. Huang, C. Yeh, W. Chang, "An accelerating CPU based correlation-based image alignment for real-time automatic optical inspection," Computers & Electrical Engineering, vol.49, pp.207-220, Jan. 2016.
  4. B.A. Draper, J.R. Beveridge, A.P.W. Bohm, C. Ross and M. Chawathe, "Implementing image applications on FPGAs," in Proc. of 2002 International Conference on Pattern Recognition, vol.3, pp.265-268, 2002.
  5. C. T. Johnston, K. T. Gribbon, and D. G Bailey, "Implementing Image Processing Algorithms on FPGAs," in Proc. of the Eleventh Electronics New Zealand Conference, ENZCon'04, pp.118-123, 2004.
  6. C. Zhao, C. Cheung, and M. Liu, "Integrated polar microstructure and template-matching method for optical position measurement," Optics Express, vol.26, vol.4, pp.4330-4345, 2018.
  7. W. Ouyang, F. Tombari, S. Mattoccia, L. Di Stefano, W.K. Cham, "Performance Evaluation of Full Search Equivalent Pattern Matching Algorithms," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, no.1, pp.127-143, Jan. 2012.
  8. S. Mattoccia, F. Tombari, L. Di Stefano, "Efficient template matching for multi-channel images," Pattern Recognition Letters, vol.32, no.5, pp.694-700, Apr. 2011.
  9. W. Shou-Der, L. Shang-Hong, "Fast Template Matching Based on Normalized Cross Correlation With Adaptive Multilevel Winner Update," IEEE Transactions on Image Processing, vol.17, no.11, pp.2227-2235, Nov. 2008.
  10. S. Sassanapitak, P. Kaewtrakulpong, "An efficient translation-rotation template matching using pre-computed scores of rotated templates," in Proc. of 2009 6th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON, pp.1040-1043, 2009.
  11. X. Cui, H. Kim, E. Park, H. Choi, "Robust and accurate pattern matching in fuzzy space for fiducial mark alignment," Machine Vision and Applications, vol.24, pp.447-459, 2013.
  12. Y. Zhang, Z. Zhang, S. Peng, D. Li, H. Xiao, C. Tang, R. Miao, L. Peng, "A rotation invariant template matching algorithm based on Sub-NCC," Mathematical Biosciences and Engineering, vol.19, no.9, pp.9505-9519, Jun. 2022.
  13. G. Kertesz, S. Szenasi and Z. Vamossy, "Performance measurement of a general multi-scale template matching method," in Proc. of 2015 IEEE 19th International Conference on Intelligent Engineering Systems (INES), pp.153-157, 2015.