Abstract
Fingerprint is a popular biometric trait for designing an automatic human recognition system. These systems are commonly benchmarked over fingerprints of the urban population whereas their practical deployment involves majority of rural population. Living standards of the rural population is not as high as urban ones. They are mostly involved in hard work and less careful about their skin conditions. Therefore, it is desirable to explore the average quality of fingerprint and the performance of automatic fingerprint recognition system for rural population. This paper analyses the (1) age-group and gender wise quality of fingerprint and (2) recognition performance under cross scanner settings. To justify the analysis, 41400 fingerprints are collected from 1150 participants living in rural areas and actively involved in physically hard work. Participants are from age group of 18 to 70 years. Samples have been collected in two phases with a gap of two months with the help of three different fingerprint scanners. Every participant has provided multiple fingerprint samples in each phase on all three scanners.
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References
NIST biometric image software, http://www.nist.gov/itl/iad/ig/nbis.cfm
Badrinath, G.S., Tiwari, K., Gupta, P.: An efficient palmprint based recognition system using 1D-DCT features. In: Huang, D.-S., Jiang, C., Bevilacqua, V., Figueroa, J.C. (eds.) ICIC 2012. LNCS, vol. 7389, pp. 594–601. Springer, Heidelberg (2012)
Cappelli, R., Ferrara, M., Maltoni, D.: Minutia cylinder-code: A new representation and matching technique for fingerprint recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(12), 2128–2141 (2010)
Chen, Y., Dass, S.C., Jain, A.K.: Fingerprint quality indices for predicting authentication performance. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 160–170. Springer, Heidelberg (2005)
Feng, J., Zhou, J., Jain, A.: Orientation field estimation for latent fingerprint enhancement. IEEE Transactions on Pattern Analysis and Machine Intelligence 35(4), 925–940 (2013)
Hong, L., Wan, Y., Jain, A.: Fingerprint image enhancement: algorithm and performance evaluation. IEEE Transactions on Pattern Analysis and Machine Intlgent. 20(8), 777–789 (1998)
Lanitis, A.: A survey of the effects of aging on biometric identity verification. Intrenational Journal of Biometrics 2(1), 34–52 (2010)
Modi, S.K., Elliott, S.J.: Impact of image quality on performance: Comparison of young and elderly fingerprints. In: Sirlantzis, K. (ed.) International Conference on Recent Advances in Soft Computing, pp. 449–454. IEEE (2006)
Singh, N., Tiwari, K., Nigam, A., Gupta, P.: Fusion of 4-slap fingerprint images with their qualities for human recognition. In: World Congress on Information and Communication Technologies, pp. 925–930. IEEE (2012)
Tiwari, K., Arya, D.K., Badrinath, G.S., Gupta, P.: Designing palmprint based recognition system using local structure tensor and force field transformation for human identification. Neurocomputing 116, 222–230 (2013)
Tiwari, K., Arya, D.K., Gupta, P.: Palmprint based recognition system using local structure tensor and force field transformation. In: Huang, D.-S., Gan, Y., Gupta, P., Gromiha, M.M. (eds.) ICIC 2011. LNCS, vol. 6839, pp. 602–607. Springer, Heidelberg (2012)
Tiwari, K., Gupta, P.: Biometrics based observer free transferable e-cash. In: ACM Workshop on Information Hiding and Multimedia Security, pp. 63–70. ACM (2014)
Tiwari, K., Gupta, P.: An efficient technique for automatic segmentation of fingerprint ROI from digital slap image. Neurocomputing (in press, 2014)
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)
Tiwari, K., Mandal, J., Gupta, P.: Segmentation of slap fingerprint images. In: Huang, D.-S., Gupta, P., Wang, L., Gromiha, M. (eds.) ICIC 2013. CCIS, vol. 375, pp. 182–187. Springer, Heidelberg (2013)
Tiwari, K., Mandi, S., Gupta, P.: A heuristic technique for performance improvement of fingerprint based integrated biometric system. In: Huang, D.-S., Bevilacqua, V., Figueroa, J.C., Premaratne, P. (eds.) ICIC 2013. LNCS, vol. 7995, pp. 584–592. Springer, Heidelberg (2013)
Tiwari, K., Siddiqui, E.A., Gupta, P.: An efficient image database encryption algorithm. In: Huang, D.-S., Gupta, P., Zhang, X., Premaratne, P. (eds.) ICIC 2012. CCIS, vol. 304, pp. 400–407. Springer, Heidelberg (2012)
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Tiwari, K., Gupta, P. (2014). Fingerprint Quality of Rural Population and Impact of Multiple Scanners on Recognition. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_22
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DOI: https://doi.org/10.1007/978-3-319-12484-1_22
Publisher Name: Springer, Cham
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