Abstract
Fingerprint is the most widely used biometric trait. Many factors may cause the quality degradation of fingerprint impressions: users, sensors and environmental facts. Most of the fingerprint-based biometric systems need an accurate prediction of fingerprint quality. A fingerprint quality measure can be used in enrollment or recognition stages, for improving the AFIS performances. In this work, a new fingerprint image quality estimation method guided by how experts classify fingerprint images quality is presented. By using six features, a continuous quality value is calculated. Experiments were performed in a well-known database. The proposed approach performance was evaluated by measuring its impact on the recognition stage and comparing it with the NFIQ quality algorithm. The Verifinger 4.2 was used as matching algorithm. The results shown that the proposed approach has a very good performance.
Chapter PDF
Similar content being viewed by others
References
Alonso-Fernandez, F., Fiérrez-Aguilar, J., Ortega-Garcia, J., Gonzalez-Rodriguez, J., Fronthaler, H., Kollreider, K., Bigün, J.: A comparative study of fingerprint image-quality estimation methods. IEEE Transactions on Information Forensics and Security 2(4), 734–743 (2007)
Awasthi, A., Venkataramani, K., Nandini, A.: Image quality quantification for fingerprints using quality-impairment assessment. In: IEEE Workshop on Applications of Computer Vision, WACV, pp. 296–302 (2013)
Bharadwaj, S., Vatsa, M., Singh, R.: Biometric quality: a review of fingerprint, iris, and face. EURASIP Journal on Image and Video Processing 2014, 34 (2014)
Chen, T.P., Jiang, X., Yau, W.Y.: Fingerprint image quality analysis. In: ICIP, pp. 1253–1256 (2004)
Kass, M., Witkin, A.P.: Analyzing oriented patterns. Computer Vision, Graphics, and Image Processing 37(3), 362–385 (1987)
Lim, E., Jiang, X., Yau, W.: Fingerprint quality and validity analysis. In: ICIP (1), pp. 469–472 (2002)
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of fingerprint recognition, 2nd edn. Springer Publishing Company, Incorporated (2009)
Munir, M.U., Javed, M.Y., Khan, S.A.: A hierarchical k-means clustering based fingerprint quality classification. Neurocomputing 85, 62–67 (2012)
Phromsuthirak, K., Areekul, V.: Fingerprint quality assessment using frequency and orientation subbands of block-based fourier transform. In: International Conference on Biometrics, ICB, pp. 1–7 (2013)
Tabassi, E., Wilson, C.L., Watson, C.I.: Fingerprint image quality. Tech. Rep. NISTIR 7151, National Institute of Standars & Technology, August 2004
Tiwari, K., Gupta, P.: No-reference fingerprint image quality assessment. In: Huang, D.-S., Jo, K.-H., Wang, L. (eds.) ICIC 2014. LNCS, vol. 8589, pp. 846–854. Springer, Heidelberg (2014)
Wu, M., Yong, A., Zhao, T., Guo, T.: A systematic algorithm for fingerprint image quality assessment. In: Huang, D.-S., Gan, Y., Gupta, P., Gromiha, M.M. (eds.) ICIC 2011. LNCS, vol. 6839, pp. 412–420. Springer, Heidelberg (2012)
Yao, Z., Bars, J.L., Charrier, C., Rosenberger, C.: Fingerprint quality assessment combining blind image quality, texture and minutiae features. In: 1st International Conference on Information Systems Security and Privacy, ICISSP, pp. 336–343 (2015)
Yao, Z., Bars, J.L., Charrier, C., Rosenberger, C.: Quality assessment of fingerprints with minutiae delaunay triangulation. In: 1st International Conference on Information Systems Security and Privacy, ICISSP, pp. 315–321 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Castillo-Rosado, K., Hernández-Palancar, J. (2015). A New Ridge-Features-Based Method for Fingerprint Image Quality Assessment. In: Pardo, A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015. Lecture Notes in Computer Science(), vol 9423. Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-25751-8_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25750-1
Online ISBN: 978-3-319-25751-8
eBook Packages: Computer ScienceComputer Science (R0)