A Method Based on the Markov Chain Monte Carlo for Fingerprint Image Segmentation

  • Xiaosi Zhan
  • Zhaocai Sun
  • Yilong Yin
  • Yun Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3614)


As one key step of the automatic fingerprint identification system (AFIS), fingerprint image segmentation can decrease the affection of the noises in the background region and handing time of the subsequence algorithms and improve the performance of the AFIS. Markov Chain Monte Carlo (MCMC) method has been applied to medicine image segmentation for decade years. This paper introduces the MCMC method into fingerprint image segmentation and brings forward the fingerprint image segmentation algorithm based on MCMC. Firstly, it generates a random sequence of closed curves as Markov Chain, which is regarded as the boundary between the fingerprint image region and the background image region and uses the boundary curve probability density function (BCPDF) as the index of convergence. Then, it is simulated by Monte Carlo method with BCPDF as parameter, which is converged to the maximum. Lastly, the closed curve whose BCPDF value is maximal is regarded as the ideal boundary curve. The experimental results indicate that the method is robust to the low-quality finger images.


Markov Chain Monte Carlo Gray Level Boundary Curve Closed Curve Image Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Jain, A.K., Uludag, U., Hsu, R.L.: Hiding a Face in a Fingerprint Image. In: Proc. ICPR, Que-bec City, pp. 756–759 (2002)Google Scholar
  2. 2.
    Zhan, X.S.: Research on Several key issues related to AFIS Based on verification mode. Ph.D Dissertation, Najing University (2003)Google Scholar
  3. 3.
    Jain, A.K., Hong, L., Bolle, R.: On-line fingerprint verification. IEEE Transactions on Pat-tern Analysis and Machine Intelligence, 302–314 (1997)Google Scholar
  4. 4.
    Mehtre, B.M., Murthy, N.N., Kapoor, S., Chatterjee, B.: Segmentation of fingerprint im-ages using the directional images. Pattern Recognition, 429–435 (1987)Google Scholar
  5. 5.
    Mehtre, B.M., Chatterjee, B.: Segmentation of fingerprint images-a composite method. Pattern Recognition, 1657–1672 (1995)Google Scholar
  6. 6.
    Chen, X., Tian, J., Cheng, J., Yang, X.: Segmentation of Fingerprint Images Using Linear Classifier. EURASIP Journal on Applied Signal Processing, 480–494 (2004)Google Scholar
  7. 7.
    Bazen, A.M., Gerez, S.H.: Segmentation of Fingerprint Images. In: Proc. Pro RISC 2000, 12th Annual Workshop on Circuits, Systems and Signal Processing, Veldhoven, The Netherlands, (November 29-30 2001)Google Scholar
  8. 8.
    Yin, Y.L., Yang, X.K., Chen, X., Wang, H.Y.: Method Based on Quadric Surface Model for Fingerprint Image Segmentation, Defense and Security. In: Proceedings of SPIE, pp. 417–324 (2004)Google Scholar
  9. 9.
    Green, P.J.: Reversible Jump Markov Chain Monte Carlo Computation and Bayesian Model Determination. Biometrika, 711–732 (1995)Google Scholar
  10. 10.
    Zhu, S.C., Zhang, R., Tu, Z.W.: Integrating Bottom- Up/ Top- Down for Object Recog-nition by Data Driven Markov Chain Monte Carlo. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 738–745. Hilton Head Island, USA (2000)Google Scholar
  11. 11.
    Tu, Z.W., Zhu, S.C., Shum, H.Y.: Image Segmentation by Data Driven Markov Chain Monte Carlo. In: Proc, ICCV 2001. Eighth IEEE International Conference on Computer Vi-sion, Canada, Vancouver, pp. 131–138 (2001)Google Scholar
  12. 12.
    Tu, Z.W., Zhu, S.C.: Parsing Images into Region and Curve Processes [EB/OL] (2002),
  13. 13.
    He, Y.L., Tian, J., Zhang, X.P.: Fingerprint Segmentation Method Based on Markov Ran-dom Field. In: Proceedings of the 4th China Graph Conference, pp. 149–156 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xiaosi Zhan
    • 1
  • Zhaocai Sun
    • 2
  • Yilong Yin
    • 2
  • Yun Chen
    • 1
  1. 1.Computer DepartmentFuyang Normal CollegeFuyangP.R. China
  2. 2.School of Computer Science & TechnologyShandong UniversityJinanP.R. China

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