Skip to main content

Pupil Contour Extraction Method of Anti-light Spot Interference for Iris Image Captured in Visible Light

  • Conference paper
Biometric Recognition (CCBR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8833))

Included in the following conference series:

Abstract

Point light sources always reflect on color iris image captured by portable color iris image capturing device, which will affect the pupil contour extraction. A pupil’s contour extraction method of anti-light spot interference is given in this paper to solve the problem. Firstly, the expanded pupil region is unfolded into a rectangle image. Secondly, all the light spot regions in the rectangle image are positioned by projecting method of axial directions after binarization and median filtering. Thirdly, these regions are filled by image inpainting technique based on fast marching method. Then, pupil contour extraction can be launched. Next, those regions which are close to contour line are repaired so that the entire exact pupil contour is finally extracted out. In addition, the experiment about this method is conducted with 200 color iris images. The results show that this method has considerable validity and adaptability.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Daugman, J.G.: Wavelet demodulation codes, statistical independence, and pattern recognition. In: Proc. 2nd Institute of Mathematics and its Applications, IMA-IP, pp. 244–260 (2000)

    Google Scholar 

  2. Daugman, J.G.: The importance of being random: statistical principles of iris recognition. Pattern Recognition 36(2), 279–291 (2003)

    Article  Google Scholar 

  3. Daugman, J.G.: Demodulation by complex-valued wavelets for stochastic pattern recognition. International Journal of Wavelets, Multiresolution and Information Processing 1(1), 1–17 (2003)

    Article  MATH  Google Scholar 

  4. Wildes, R.: Iris recognition: An emerging biometric technology. Proc. IEEE 85(9), 1348–1363 (1997)

    Article  Google Scholar 

  5. Ma, L., Zhang, D., Li, N., Cai, Y., Zuo, W., Wang, K.: Iris-based medical analysis by geometric deformation features. IEEE Journal of Biomedical and Health Informatics 17(1) (January 2013)

    Google Scholar 

  6. Tian, Q., Pan, Q., Cheng, Y.: Study on iris boundary positioning in different illumination. Journal of Optoelectronics ∙ Laser 17(4), 488–492 (2006)

    Google Scholar 

  7. Wu, J., Zou, D., Li, J.: Fast and accurate iris location algorithm. Chinese Journal of Scientific Instrument 28(8), 1469–1473 (2007)

    Google Scholar 

  8. Yang, L., Xia, L., Na, W., et al.: An improved iris location algorithm based on sampling to special regions of interesting. Acta Photonia Sinica 37(6), 1277–1280 (2008)

    Google Scholar 

  9. Yuan, W., Xu, L., Lin, Z.: Iris positioning algorithm based on gray distribution features of eye images. Journal of Optoelectronics ∙ Laser 17(2), 226–230 (2006)

    Google Scholar 

  10. Yuan, W., Xu, L., Lin, Z.: An iris block-encoding method based on statistic of local information. Acta Optica Sinica 27(11), 2047–2053 (2007)

    Google Scholar 

  11. Nam, K.W., Yoon, K.L., Yang, W.S.: A feature extraction method for binary iris code construction. In: Proceedings of the 2nd International Conference on Information Technology for Application (ICITA 2004), Harbin, pp. 284–287 (2004)

    Google Scholar 

  12. Li, X., Yu, L., Wang, N.: A fast iris location algorithm based on line detection. Journal of Computer-Aided Design & Computer Graphics 18(8), 1155–1159 (2006)

    MathSciNet  Google Scholar 

  13. Yuan, W., Bai, X.: A new iris edge extraction method. Acta Photonia Sinica 8(29), 2158–2163 (2009)

    Google Scholar 

  14. Telea, A.: An image inpainting technique based on the fast marching method. Journal of Graphics Tools 9(1), 25–36 (2004)

    Article  Google Scholar 

  15. Liu, W., Fan, Y., Lei, T.: Eye corneal reflection removal based on boundary initial position detection. Computer Engineering and Applications 49(17), 1–5 (2013)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Yu, X., Song, J., Yuan, W. (2014). Pupil Contour Extraction Method of Anti-light Spot Interference for Iris Image Captured in Visible Light. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12484-1_38

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12483-4

  • Online ISBN: 978-3-319-12484-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics