Abstract
Biometric systems are being widely used today for automated authentication purposes. In particular, vascular biometrics or vein recognition is receiving a large amount of attention because of its several advantages related to security and convenience. However, images containing vein patterns normally include more information than just those structural arrangements. Thus, we propose a finger-vein biometric system based exclusively on textural features to evaluate the usefulness of the remaining information around vein patters. Textural features are obtained through gray-level co-occurrence matrices from the wavelet detail coefficients belonging to finger-vein images. The evaluation of the proposed biometric system is based on a standardized finger-vein database and its results show favorable improvements on the finger-vein authentication accuracy when textural features are incorporated in the biometric process.
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References
Kaur, G., Singh, G., Kumar, V.: A review on biometric recognition. Int. J. BioSci. BioTechnol. 6, 69–76 (2014)
Wang, P., Sun, D.: A research on palm vein recognition. In: 2016 IEEE 13th International Conference on Signal Processing (ICSP), pp. 1347–1351. IEEE (2016)
Syazana-Itqan, K., Syafeeza, A., Saad, N., Hamid, N.A., Saad, W.H.B.M.: A review of finger-vein biometrics identification approaches. Indian J. Sci. Technol, 9 (2016)
Yang, L., Yang, G., Yin, Y., Xi, X.: Finger vein recognition with anatomy structure analysis. IEEE Transactions on Circuits and Systems for Video Technology (2017)
Cheng, Y.C., Chen, H., Cheng, B.C.: Special point representations for reducing data space requirements of finger-vein recognition applications. Multimedia Tools Appl. 76, 11251–11271 (2017)
Bansal, K., Kaur, S.: Finger vein recognition using minutiae extraction and curve analysis. Int. J. Sci. Res. 4, 2402–2405 (2015)
Beura, S., Majhi, B., Dash, R.: Mammogram classification using two dimensional discrete wavelet transform and gray-level co-occurrence matrix for detection of breast cancer. Neurocomputing 154, 1–14 (2015)
Etehadtavakol, M., Ng, E., Chandran, V., Rabbani, H.: Separable and non-separable discrete wavelet transform based texture features and image classification of breast thermograms. Infrared Phys. Technol. 61, 274–286 (2013)
Yin, Y., Liu, L., Sun, X.: SDUMLA-HMT: a multimodal biometric database. In: Sun, Z., Lai, J., Chen, X., Tan, T. (eds.) CCBR 2011. LNCS, vol. 7098, pp. 260–268. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25449-9_33
Modi, S.K.: Biometrics in identity management: concepts to applications. Artech House, Massachusetts (2011)
Chen, C.H.: Handbook of pattern recognition and computer vision. World Scientific, New Jersey (2015)
Marsland, S.: Machine learning: an algorithmic perspective. CRC Press, Florida (2015)
Trabelsi, R.B., Masmoudi, A.D., Masmoudi, D.S.: A new multimodal biometric system based on finger vein and hand vein recognition. Int. J. Eng. Technol. 4, 3175 (2013)
Lu, Y., Yoon, S., Park, D.S.: Finger vein recognition based on matching score-level fusion of Gabor features. J. Korean Inst. Commun. Inf. Sci. 38, 174–182 (2013)
Lu, Y., Xie, S.J., Yoon, S., Park, D.S.: Finger vein identification using polydirectional local line binary pattern. In: 2013 International Conference on ICT Convergence (ICTC), pp. 61–65. IEEE (2013)
Acknowledgment
This work was partially supported by the Universidad de las Fuerzas Armadas ESPE under Research Grant 2015-PIC-004.
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Carrera, E.V., Izurieta, S., Carrera, R. (2018). A Finger-vein Biometric System Based on Textural Features. In: Rocha, Á., Guarda, T. (eds) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-73450-7_35
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DOI: https://doi.org/10.1007/978-3-319-73450-7_35
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