An Efficient Fingerprint Image Thinning Algorithm

Davit Kocharyan

doi:doi:10.11648/j.ajsea.20130201.11

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An Efficient Fingerprint Image Thinning Algorithm

Davit Kocharyan

Published in American Journal of Software Engineering and Applications (Volume 2, Issue 1)

Received: 30 January 2013 Accepted: Published: 20 February 2013

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Abstract

Most fingerprint recognition applications rely heavily on efficient and fast image enhancement algorithms. Image thinning is a very important stage of image enhancement. A good thinning algorithm preserves the structure of the original fingerprint image, reduces the amount of data needed to process and helps improve the feature extraction accuracy and efficiency. In this paper we describe and compare some of the most used fingerprint thinning algorithms. Results show that faster algorithms have difficulty preserving connectivity. Zhang and Suen’s algorithm gives the least processing time, while Guo and Hall’s algorithm produces the best skeleton quality. A modified Zhang and Suen’s algorithm is proposed, that is efficient and fast, and better preserves structure and connectivity.

Published in	American Journal of Software Engineering and Applications (Volume 2, Issue 1)
DOI	10.11648/j.ajsea.20130201.11
Page(s)	1-6
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Image Thinning; Fingerprint Recognition; Minutiae; Image Enhancement

References

[1]	Davide Maltoni, Dario Maio, Handbook of Fingerprint Recognition, Springer, 2009.
[2]	Z. Guo and R. Hall, "Parallel thinning with two-subiteration algorithms,"Communications of the ACM, vol. 32, pp. 359–373, Mar 1989.
[3]	R. Gupta and R. Kaur, "Skeletonization algorithm for numerical patterns", International Jornal of Signal Processing, Image Processing andPattern Recognition, vol. 01, pp. 63–72, Dec 2008.
[4]	T. Zhang and C. Suen, "A fast parallel algorithm for thinning digital patterns," Communications of the ACM, vol. 27, pp. 236–239, Mar 1984.
[5]	W. Abdulla, A. Saleh, and A. Morad, "A preprocessing algorithm for hand-written character recognition",Pattern Recognition Letters 7, pp. 13–18, 1988.
[6]	R. Hall, "Fast parallel thinning algorithms: Parallel speed and connectivity preservation," Communications of the ACM, vol. 32, pp. 124–129, Jan 1989.
[7]	B. Jang and T. Chin, "One-pass parallel thinning: Analysis, properties, and quantitative evaluation," IEEE Transactions on Pattern Analysis andMechine Intelligence, pp. 1129–1140, 1992.
[8]	G. Raju and Y. Xu, "Study of parallel thinning algorithms," IEEE International Conference on Systems, Man, and Cybernetics, vol. 01,pp. 661–666, Dec 1991.
[9]	S. Prabhakar, A. K. Jain and S. Pankanti, "Learning fingerprint minutiae location and type", Pattern Recognition, 36(8): 1847–1857, 2003.
[10]	Kalyani Mali, Samayita Bhattacharya, Fingerprint Recognition Using Global and Local Structures, International Journal on Computer Science and Engineering, Vol. 3 No. 1 Jan 2011.Ratha, Nalini; Bolle, Ruud, "Automatic Fingerprint Recognition Systems", Springer, XVII, 458 p. 135.
[11]	James L. Wayman (Editor), Anil K. Jain, "Biometric Systems", Springer, 2004.
[12]	Bir Bhanu,Xuejun Tan, "Computational Algorithms for Fingerprint Recognition", Springer, 2004.

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Davit Kocharyan. (2013). An Efficient Fingerprint Image Thinning Algorithm. American Journal of Software Engineering and Applications, 2(1), 1-6. https://doi.org/10.11648/j.ajsea.20130201.11

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ACS Style

Davit Kocharyan. An Efficient Fingerprint Image Thinning Algorithm. Am. J. Softw. Eng. Appl. 2013, 2(1), 1-6. doi: 10.11648/j.ajsea.20130201.11

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AMA Style

Davit Kocharyan. An Efficient Fingerprint Image Thinning Algorithm. Am J Softw Eng Appl. 2013;2(1):1-6. doi: 10.11648/j.ajsea.20130201.11

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@article{10.11648/j.ajsea.20130201.11,
  author = {Davit Kocharyan},
  title = {An Efficient Fingerprint Image Thinning Algorithm},
  journal = {American Journal of Software Engineering and Applications},
  volume = {2},
  number = {1},
  pages = {1-6},
  doi = {10.11648/j.ajsea.20130201.11},
  url = {https://doi.org/10.11648/j.ajsea.20130201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20130201.11},
  abstract = {Most fingerprint recognition applications rely heavily on efficient and fast image enhancement algorithms. Image thinning is a very important stage of image enhancement. A good thinning algorithm preserves the structure of the original fingerprint image, reduces the amount of data needed to process and helps improve the feature extraction accuracy and efficiency. In this paper we describe and compare some of the most used fingerprint thinning algorithms. Results show that faster algorithms have difficulty preserving connectivity. Zhang and Suen’s algorithm gives the least processing time, while Guo and Hall’s algorithm produces the best skeleton quality. A modified Zhang and Suen’s algorithm is proposed, that is efficient and fast, and better preserves structure and connectivity.},
 year = {2013}
}

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TY  - JOUR
T1  - An Efficient Fingerprint Image Thinning Algorithm
AU  - Davit Kocharyan
Y1  - 2013/02/20
PY  - 2013
N1  - https://doi.org/10.11648/j.ajsea.20130201.11
DO  - 10.11648/j.ajsea.20130201.11
T2  - American Journal of Software Engineering and Applications
JF  - American Journal of Software Engineering and Applications
JO  - American Journal of Software Engineering and Applications
SP  - 1
EP  - 6
PB  - Science Publishing Group
SN  - 2327-249X
UR  - https://doi.org/10.11648/j.ajsea.20130201.11
AB  - Most fingerprint recognition applications rely heavily on efficient and fast image enhancement algorithms. Image thinning is a very important stage of image enhancement. A good thinning algorithm preserves the structure of the original fingerprint image, reduces the amount of data needed to process and helps improve the feature extraction accuracy and efficiency. In this paper we describe and compare some of the most used fingerprint thinning algorithms. Results show that faster algorithms have difficulty preserving connectivity. Zhang and Suen’s algorithm gives the least processing time, while Guo and Hall’s algorithm produces the best skeleton quality. A modified Zhang and Suen’s algorithm is proposed, that is efficient and fast, and better preserves structure and connectivity.
VL  - 2
IS  - 1
ER  -

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Author Information

Davit Kocharyan

Digital Signal and Image Processing Laboratory; Institute for Informatics and Automation Problems of NAS RA, Yerevan, Armenia

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Davit Kocharyan. (2013). An Efficient Fingerprint Image Thinning Algorithm. American Journal of Software Engineering and Applications, 2(1), 1-6. https://doi.org/10.11648/j.ajsea.20130201.11

Copy | Download

ACS Style

Davit Kocharyan. An Efficient Fingerprint Image Thinning Algorithm. Am. J. Softw. Eng. Appl. 2013, 2(1), 1-6. doi: 10.11648/j.ajsea.20130201.11

Copy | Download

AMA Style

Davit Kocharyan. An Efficient Fingerprint Image Thinning Algorithm. Am J Softw Eng Appl. 2013;2(1):1-6. doi: 10.11648/j.ajsea.20130201.11

Copy | Download

@article{10.11648/j.ajsea.20130201.11,
  author = {Davit Kocharyan},
  title = {An Efficient Fingerprint Image Thinning Algorithm},
  journal = {American Journal of Software Engineering and Applications},
  volume = {2},
  number = {1},
  pages = {1-6},
  doi = {10.11648/j.ajsea.20130201.11},
  url = {https://doi.org/10.11648/j.ajsea.20130201.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20130201.11},
  abstract = {Most fingerprint recognition applications rely heavily on efficient and fast image enhancement algorithms. Image thinning is a very important stage of image enhancement. A good thinning algorithm preserves the structure of the original fingerprint image, reduces the amount of data needed to process and helps improve the feature extraction accuracy and efficiency. In this paper we describe and compare some of the most used fingerprint thinning algorithms. Results show that faster algorithms have difficulty preserving connectivity. Zhang and Suen’s algorithm gives the least processing time, while Guo and Hall’s algorithm produces the best skeleton quality. A modified Zhang and Suen’s algorithm is proposed, that is efficient and fast, and better preserves structure and connectivity.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - An Efficient Fingerprint Image Thinning Algorithm
AU  - Davit Kocharyan
Y1  - 2013/02/20
PY  - 2013
N1  - https://doi.org/10.11648/j.ajsea.20130201.11
DO  - 10.11648/j.ajsea.20130201.11
T2  - American Journal of Software Engineering and Applications
JF  - American Journal of Software Engineering and Applications
JO  - American Journal of Software Engineering and Applications
SP  - 1
EP  - 6
PB  - Science Publishing Group
SN  - 2327-249X
UR  - https://doi.org/10.11648/j.ajsea.20130201.11
AB  - Most fingerprint recognition applications rely heavily on efficient and fast image enhancement algorithms. Image thinning is a very important stage of image enhancement. A good thinning algorithm preserves the structure of the original fingerprint image, reduces the amount of data needed to process and helps improve the feature extraction accuracy and efficiency. In this paper we describe and compare some of the most used fingerprint thinning algorithms. Results show that faster algorithms have difficulty preserving connectivity. Zhang and Suen’s algorithm gives the least processing time, while Guo and Hall’s algorithm produces the best skeleton quality. A modified Zhang and Suen’s algorithm is proposed, that is efficient and fast, and better preserves structure and connectivity.
VL  - 2
IS  - 1
ER  -

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