Skip to main content

A Binarization Approach for Wafer ID Based on Asterisk-Shape Filter

  • Chapter

Part of the book series: Studies in Computational Intelligence ((SCI,volume 214))

Abstract

The binarization of wafer ID image is one of the key techniques of wafer ID recognition system and its results influence the accuracy of the segmentation of characters and their identification directly. The process of binarization of wafer ID is similar to that of the car license plate characters. However, due to some unique characteristics, such as the unsuccessive strokes of wafer ID, it is more difficult to make of binarization of wafer ID than the car license plate characters. In this paper, a wafer ID recognition scheme based on asterisk-shape filter is proposed to cope with the serious influence of uneven luminance. The testing results show that our proposed approach is efficient even in situations of overexposure and underexposure the wafer ID with high performance.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Kittler, J., Illingworth, J.: On Threshold Selection Using Clustering Criteria. IEEE Transactions on Systems, Man, and Cybernetics 15, 652–655 (1985)

    Google Scholar 

  2. Brink, A.D.: Thresholding of digital images using two-dimensional entropies. Pattern Recognition 25, 803–808 (1992)

    Article  Google Scholar 

  3. Yan, H.: Unified formulation of a class of image thresholding techniques. Pattern Recognition 29, 2025–2032 (1996)

    Article  Google Scholar 

  4. Sauvola, J., Pietikainen, M.: Adaptive document image binarization. Pattern Recognition 33, 225–236 (2000)

    Article  Google Scholar 

  5. Trier, O.D., Jain, A.K.: Goal-Directed Evaluation of Binarization Methods. IEEE Transactions On Pattern Analysis And Machine Intelligence, 1191–1201 (1995)

    Google Scholar 

  6. Gatos, B., Pratikakis, I., Perantonis, S.J.: Adaptive degraded document image binarization. Pattern Recognition 39, 317–327 (2006)

    Article  MATH  Google Scholar 

  7. Sheikh, L.M., Hassan, I., Sheikh, N.Z., Bashir, R.A., Khan, S.A., Khan, S.S.: An adaptive multi-thresholding technique for binarization of color images. In: Proceedings of the 9th WSEAS International Conference on Computers table of contents (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Wei-Chih, H., Tsan-Ying, Y., Kuan-Liang, C. (2009). A Binarization Approach for Wafer ID Based on Asterisk-Shape Filter. In: Chien, BC., Hong, TP. (eds) Opportunities and Challenges for Next-Generation Applied Intelligence. Studies in Computational Intelligence, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92814-0_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-92814-0_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92813-3

  • Online ISBN: 978-3-540-92814-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics