Abstract
Fingerprints are the best biometric identity mark due to the consistency during life time and uniqueness. To increase the classification accuracy of fingerprint images, it is necessary to improve image quality which is a key role for correct recognition. In other words, enhancing the fingerprint images leads us to obtain better results in classification of fingerprint images. Although Gabor filter and fast Fourier transform (FFT) are used to enhance fingerprint images, Gabor filter acts better than FFT in detection of incorrect ridge endings and ridge bifurcation, while FFT tries to connect broken ridges together and fill the created holes. This paper tries to enhance gray-scale fingerprint images by combining the Gabor filter and FFT in order to get benefit from the advantages of each enhancing filter (Gabor filter and FFT). A method is proposed for fingerprint image segmentation based on the image histogram and density. By employing the proposed method which enhances the fingerprint images using the better enhancing filter in each part, the experimental results show that the whole finger print is better enhanced, and consequently, it leads to a better recognition rate.
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Zhang, Q., Yan, H.: Fingerprint Classification Based on Extraction and Analysis of Singularities and Pseudo Ridges, vol. 37, pp. 2233–2243. University of Sydney, Australia (2003)
Thai, R.: Fingerprint Image Enhancement and Minutiae. University of Western Australia, Australia (2003)
Hong, L., Wan, Y., Jain, A.: Fingerprint image enhancement: algorithm and performance evaluation. Pattern Anal. Mach. Intell. In: IEEE Trans. 20, 777–789 (1998)
Maltoni, D., Maio, D., Jain, A., Prabhakar, S.: Handbook of Fingerprint Recognition, 2nd edn. Springer Publishing Company, Berlin (2009). ISBN 1848822537
Greenberg, S., Aladjem, M., Kogan, D., Dimitrov, I.: Finger print image enhancement using filtering techniques. Pattern Recogn. 3, 227–236 (2000)
Yun, E., Cho, S.: Adaptive Fingerprint Image Enhancement with Fingerprint Image Quality Analysis, vol. 24. Yonsei University, Seoul (2005)
Zhu, E., Yin, J., Zhang, G., Hu, C.: A Gabor filter based fingerprint enhancement scheme using average frequency. World Sci. J. 20, 417–429 (2006)
Ryu, Ch., Kong, S.G., Kim, H.: Enhancement of feature extraction for low-quality fingerprint images using stochastic resonance Filter. Pattern Recogn. Lett. 32, 107–113 (2011)
Hong, L., Jain, A.: Classification of fingerprint images. In: Proceedings of the 11th Scandinavian Conference on Image Analysis, pp. 7–11. Michigan State University, Kangerlussuaq (1999)
Julasayvake, A., Choomchuay, S.: A Combined Technique in Fingerprint Core point Detection. In: Proceedings of the International Workshop on Advanced Image Technology, pp. 556–561. Thailand (2007)
Wang, S., Wang, Y.: Finger print enhancement in the singular point area. Signal Process. Lett. 11, 16–19 (2004)
Jain, A.K., Prabhakar, S., Hong, L., Pankanti, S.: Filter bank-based fingerprint matching. Image Process. 9, 846–859 (2000)
Lei, G., Da-hai, C., Hai, L., Jing, C.: Characteristic preserving binarization for fingerprint image. In: Image and Graphics, Fourth International Conference, pp. 401–408 (2007)
Feng, J., Jain, A.K.: Filtering large fingerprint database for latent matching. In: Pattern Recognition, In: IEEE, 19th International Conference, pp. 1–4. Michigan State University (2008)
Tantaratana, S., Areekul, V., Watchareeruetai, U.: Separable Gabor Filter Realization for Fast Fingerprint Enhancement, vol. 3, pp. III-253-6. In: IEEE, Italy (2005)
Rajinikannan, M., Ashok Kumar, D., Muthuraj, R.: Estimating the impact of fingerprint image enhancement algorithms for better minutia detection. Int. J. Comput. Appl. 2(1), 36–42 (2010)
Jang, W., Park, D., Lee, D.: Fingerprint image enhancement based on a half Gabor filter. Lecture Notes Comput. Sci. 3832, 258–264 (2005)
Wang, W., Li, J., Huang, F., Feng, H.: Design and implementation of Log-Gabor filter in fingerprint image enhancement. Pattern Recogn. Lett. 29, 301–308 (2007)
Cavusogle, A., Gorgunogle, S.: A fast fingerprint image enhancement algorithm using a parabolic mask. Comput. Electr. Eng. 34, 250–256 (2007)
Yang, J., Liu, L., Jiang, T., Fan, Y.: A modified Gabor filter design method for fingerprint image enhancement. Pattern Recogn. Lett. 24, 1805–1817 (2003)
Areekul, V., Watchareeruetai, U., Tantaratana, S.: Fast separable Gabor filter for fingerprint enhancement. In: 2004 Proceeding International Conference on Biometric Authentication, LNCS3072. pp. 403–409. Springer, Berlin
Kant, C., Nath, R.: Reducing process-time for fingerprint identification system. Int. J. Biom. Bioinf. 3, 1–9 (2009)
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Zahedi, M., Ghadi, O.R. Combining Gabor filter and FFT for fingerprint enhancement based on a regional adaption method and automatic segmentation. SIViP 9, 267–275 (2015). https://doi.org/10.1007/s11760-013-0436-3
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DOI: https://doi.org/10.1007/s11760-013-0436-3