A fingerprint matching algorithm

Бесплатный доступ

Fingerprint pattern knowledge is largely applied in many fields such as access control and identity administration. This is however associated with some problem of automatic fingerprint recognition and therefore this has rendered to the use of the most known method that is biometric identification. Every finger of the hand shows a different pattern of ridges and depression different from the other finger and this pattern remains sole and constant thus helping in identity since fingerprint pattern from one person is different to that of another person. This pattern may alter whenever there are cuts and bruises in the outer part of the finger. Fingerprint pattern recognition method includes the following steps: firstly, matching of the fingerprint which includes the pattern based method and the minutiae method. Secondly, the used algorithm in the recognition and comparing of the fingerprint images. Thirdly, the image enhancement process that helps to improve the quality of the fingerprint pattern and forth the reduction of the size of the image which includes identification of the region of small minutiae and actual minutiae. The objective of this research is recognition of the fingerprint pattern.

Еще

Fingerprint matching, image enhancement, segmentation, gabor filter

Короткий адрес: https://sciup.org/147232285

IDR: 147232285   |   DOI: 10.14529/ctcr190404

Список литературы A fingerprint matching algorithm

  • Liu N., Yin Y., Zhang H. A Fingerprint Matching Algorithm Based On Delaunay Triangulation Net 1 // The Fifth International Conference on Computer and Information Technology (CIT'05). Shanghai, China: IEEE, 2005, pp. 591-595.
  • Francis-Lothai F., Bong D.B.L. A Fingerprint Matching Algorithm using Bit-Plane Extraction Method with Phase-Only Correlation // Int. J. Biom, 2017, vol. 9, no. 1, pp. 44-66. DOI: 10.1504/IJBM.2017.084135
  • Narwal S., Kaur D. Comparison between Minutiae Based and Pattern Based Algorithm of Fingerprint Image // International Journal of Information Engineering and Electronic Business, 2016, 8 (2), pp. 23-29. DOI: 10.5815/ijieeb.2016.02.03
  • Balti A., Sayadi M., Fnaiech F. Invariant and reduced features for Fingerprint Characterization // IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society. Montreal, QC, Canada: IEEE, 2012, pp. 1530-1534. DOI: 10.1109/IECON.2012.6388514
  • Ganbawle A., Shaikh P.J.A. Implementation of Fingerprint Matching Algorithm // Int. J. Eng. Tech., 2016, vol. 2, no. 2, pp. 42-47.
  • Palanichamy J., Marimuthu R. A Novel Image Alignment and a Fast Efficient Localized Euclidean Distance Minutia Matching Algorithm for Fingerprint Recognition System // Int. Arab J. Inf. Technol., 2016, vol. 13, no. 6B, pp. 1061-1067.
  • Peralta D. et al. A Survey on Fingerprint Minutiae-based Local Matching for Verification and Identification: Taxonomy and Experimental Evaluation // Inf. Sci. (Ny). Elsevier Inc., 2015, vol. 315, pp. 67-87.
  • DOI: 10.1016/j.ins.2015.04.013
  • Ahmed T., Sarma M. An Advanced Fingerprint Matching Using Minutiae-based Indirect Local Features // Multimed. Tools Appl. Springer US, 2017, vol. 77, no. 15, pp. 19931-19950.
  • DOI: 10.1007/s11042-017-5444-9
  • Jain A.K., Feng J., Nandakumar K. Fingerprint Matching // Computer (Long. Beach. Calif), 2010, vol. 43, no. 2, pp. 36-44.
  • DOI: 10.1109/MC.2010.38
  • Win Z.M., Sein M.M. An Efficient Fingerprint Matching System for Low Quality Images // Int. J. Comput. Appl., 2011, vol. 26, no. 4, pp. 12.
  • DOI: 10.5120/3094-4246
  • Dyre S., Sumathi C.P. A Survey on Various Approaches to Fingerprint Matching for Personal Verification and Identification // Int. J. Comput. Sci. Eng. Surv, 2016, vol. 7, no. 4, pp. 1-17.
  • DOI: 10.5121/ijcses.2016.7401
  • Afsar F.A., Arif M., Hussain M. Fingerprint Identification and Verification System using Minutiae Matching // National Conference on Emerging Technologies, 2004, pp. 141-146.
  • Patel H., Asrodia P. Fingerprint Matching Using Two Methods // Int. J. Eng. Res. Appl., 2012, vol. 2, no. 3, pp. 857-860.
  • Ram S., Bischof H., Birchbauer J. Curvature Preserving Fingerprint Ridge Orientation Smoothing Using Legendre Polynomials // 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. Anchorage, AK, USA: IEEE, 2008, pp. 1-8.
  • DOI: 10.1109/CVPRW.2008.4563118
  • Jie Y. et al. Fingerprint Minutiae Matching Algorithm for Real Time System // Pattern Recognit. Soc., 2006, vol. 39, no. 1, pp. 143-146.
  • DOI: 10.1016/j.patcog.2005.08.005
  • Jain A., Ross A., Prabhakar S. Fingerprint Matching Using Minutiae and Texture Features // Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205). Thessaloniki, Greece: IEEE, 2001, pp. 282-285.
  • Peralta D. et al. Minutiae Filtering to Improve both Efficacy and Efficiency of Fingerprint Matching Algorithms // Eng. Appl. Artif. Intell., 2014, vol. 32. pp. 37-53.
  • DOI: 10.1016/j.engappai.2014.02.016
  • Jain A.K., Feng J. Latent Fingerprint Matching // IEEE Trans. Pattern Anal. Mach. Intell., 2011, vol. 33, no. 1, pp. 88-100.
  • DOI: 10.1109/TPAMI.2010.59
  • Pamplona Segundo, Lemes M. and de P.R. Pore Based Ridge Reconstruction for Matching // The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2015, pp. 128-133.
  • DOI: 10.1109/CVPRW.2015.7301328
  • Kaur M. et al. Fingerprint Verification System using Minutiae Extraction Technique // Int. J. Comput. Electr. Autom. Control Inf. Eng., 2008, vol. 2, no. 10, pp. 3405-3410.
  • Mohammedsayeemuddin S., Pithadia P. V, Vandra D. A Simple and Novel Fingerprint Image Segmentation Algorithm // 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT). Ghaziabad, India: IEEE, 2014, pp. 756-759.
  • DOI: 10.1109/ICICICT.2014.6781375
Еще
Статья научная