Abstract
The proposed work is to enhance the features of the fingerprint image using steerable filter in wavelet domain to increase the accuracy and speed of Automatic fingerprint identification system. The proposed method uses steerable filter and wavelet. The steerable filter allows filtering process adaptively to any orientation and determining analytically the filter output as a function of orientation and the wavelet domain speeds up the computation process. The steerable filter is applied on each local blocks of approximation image of wavelet transform for tuning up the fingerprint image features and then smoothing the resultant which leads to enhanced image. Experiments are conducted on FVC databases and results show that enhancement process reveals clear visualization of fingerprint images.
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References
Blotta, E., Moler, E.: Fingerprint image enhancement by differential hysteresis processing. Forensic Sci. Int. 141(2), 109–113 (2004)
Cavusoglu, A., Gorgunoglu, S.: A fast fingerprint image enhancement algorithm using a parabolic mask. Comput. Electr. Eng. 34(3), 250–256 (2008)
Cheng, J., Tian, J.: Fingerprint enhancement with dyadic scale-space. Pattern Recognit. Lett. 25(11), 1273–1284 (2004)
Chikkerur, S., Cartwright, A.N., Govindaraju, V.: Fingerprint enhancement using STFT analysis. Pattern Recognit. 40(1), 198–211 (2007)
Feng, X.G., Milanfar, P.: Multiscale principal components analysis for image local orientation estimation. IEEE Signals Syst. Comput. 1, 478–482 (2002)
Freeman, W.T., Adelson, E.H.: The design and use of steerable filter. IEEE Trans. Pattern Anal. Mach. Intell. 13(9), 891–906 (1991)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn, p. 717. Pearson Education India, New Jersey (2009). Image Analysis
Gottschlich, C.: Curved-region-based ridge frequency estimation and curved Gabor filters for fingerprint image enhancement. IEEE Trans. Image Process. 21(4), 2220–2227 (2012)
Hong, L., Wan, Y., Jain, A.: Fingerprint image enhancement: algorithm and performance evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 20(8), 777–789 (1998)
Hsieh, C.-T., Lai, E., Wang, Y.-C.: An effective algorithm for fingerprint image enhancement based on wavelet transform. Pattern Recognit. 36(2), 303–312 (2003)
Yang, J., Liu, L., Jiang, T., Fan, Y.: A modified Gabor filter design method for fingerprint image enhancement. Pattern Recognit. Lett. 24(12), 1805–1817 (2003)
Maltoni, D., Maio, D., Jain, A., Prabhakar, S.: Handbook of Fingerprint Recognition, p. 103. Springer Science & Business Media, London (2009)
Paul, A.M., Lourde, R.M.: A study on image enhancement techniques for fingerprint identification. In: IEEE International Conference on Video and Signal Based Surveillance, p. 16 (2006)
Ratha, N.K., Chen, S., Jain, A.K.: Adaptive flow orientation-based feature extraction in fingerprint image. Pattern Recognit. 28(11), 1657–1672 (1995)
Shi, Z., Govindaraju, V.: A chaincode based scheme for fingerprint feature extraction. Pattern Recogni. Lett. 27(5), 462–468 (2006)
Wang, W., Li, J., Huang, F., Feng, H.: Design and implementation of Log-Gabor filter in fingerprint image enhancement. Pattern Recognit. Lett. 29(3), 301–308 (2008)
Wu, C., Tulyakov, S., Govindaraju, V.: Robust point-based feature fingerprint segmentation algorithm. In: Lee, S.-W., Li, S.Z. (eds.) International Conference on Biometrics. LNCS, vol. 4642, pp. 1095–1103. Springer, Heidelberg (2007)
Wu, C., Shi, Z., Govindaraju, V.: Fingerprint image enhancement method using directional median filter. In: Proceedings of SPIE, vol. 5404, p. 67 (2004)
Yang, J., Liu, L., Jiang, T., Fan, Y.: An effective algorithm for fingerprint image enhancement based on wavelet transform. Pattern Recognit. 36(2), 303–312 (2003)
Yang, J., Xiong, N., Vasilakos, A.V.: Two-stage enhancement scheme for low quality fingerprint images by learning from the images. IEEE Trans. Hum. Mach. Syst. 43(2), 235–248 (2013)
Ye, Q., Xiang, M., Cui, Z.: Fingerprint image enhancement algorithm based on two dimension EMD and Gabor filter. Procedia Eng. 29, 1840–1844 (2012)
Zhang, W., Tang, Y.Y., You, X.: Fingerprint enhancement using wavelet transform combined with Gabor filter. Int. J. Pattern Recognit. Artif. Intell. 18(8), 1391–1406 (2004)
FVC2000 Set B Databases. http://bias.csr.unibo.it/fvc2000/download.asp
FVC2002 Set B Databases. http://bias.csr.unibo.it/fvc2002/download.asp
FVC2004 Set B Databases. http://bias.csr.unibo.it/fvc2004/download.asp
Acknowledgement
This work is funded by University Grants Commission Major Research Project (MRP: F.No. 42-144/2013(SR)), New Delhi, INDIA
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Jeyalakshmi, K.S., Kathirvalavakumar, T. (2018). Fingerprint Image Enhancement Using Steerable Filter in Wavelet Domain. In: Abraham, A., Muhuri, P., Muda, A., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2017. Advances in Intelligent Systems and Computing, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-76348-4_31
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DOI: https://doi.org/10.1007/978-3-319-76348-4_31
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