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Efficient biometric palm-print matching on smart-cards for high security and privacy

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Abstract

Smart control access to any service is at the very basis of any smart city project. Biometrics have been used as a solution for system access control, for many years now. However, the simple use of biometrics can not be considered as final and perfect solution. Most problems are related to the data transmission way between the medias, where the users require access and the servers where the biometric data, captured upon registration, are stored. In this paper, the use smart-cards is adopted as a possible effective yet efficient solution to this problem. Palm-prints have been used as a human identifier for a long time now. This biometric is considered one of the most reliable to distinguish a person from another as its unique yet stable over time. In this work, we propose an efficient implementation of palm-print verification on smart-cards. For this implementation, the matching is done on-card. Thus, the biometric characteristics are always kept in the owner’s card, guaranteeing the maximum security and privacy. In a first approach, the False Acceptance Rate (FAR) and False Rejection Rate (FRR) are improved using upward, downward, leftward and rightward translations of the matched palm-codes. However, after thorough analysis of the achieved results, we show that the proposed method introduces a significant increase in terms of execution time of the matching operation. In order to mitigate this impact, we augmented the proposed technique with an acceptance threshold verification, thus decreasing drastically the execution time of the matching operation, and yet achieving considerably low FAR and FRR. It is noteworthy to point out that these characteristics are at the basis of any access control successful usage.

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Notes

  1. Table is taken from [18], where L, M and H represent low, medium and high, respectively. The results are based on the perception of the authors.

References

  1. Alsmirat M, Jararweh Y, Al-Ayyoub M, Shehab MA, Gupta BB (2016) Accelerating compute intensive medical imaging segmentation algorithms using gpus. Multimedia Tools and Applications

  2. Alsmirat MA, Jararweh Y, Obaidat I, Gupta BB (2016) Automated wireless video surveillance framework: Design and evaluation. Journal of Real-Time Image Processing

  3. Ashbaugh DR (1999) Quantitative-qualitative friction ridge analysis: an introduction to basic and advanced ridgeology. CRC press, Boca Raton, Estados Unidos

    Book  Google Scholar 

  4. Atawneh S, Almomani A, Al Bazar H, Sumari P, Gupta B (2016) Secure and imperceptible digital image steganographic algorithm based on diamond encoding in dwt domain. Multimedia tools and applications

  5. Daugman JG (1980) Two-dimensional spectral analysis of cortical receptive field profiles. Vis Res 20(10):847–856

    Article  Google Scholar 

  6. Daugman JG (1993) High confidence visual recognition of persons by a test of statistical independence. IEEE Trans Pattern Anal Mach Intell 15(11):1148–1161

    Article  Google Scholar 

  7. Daugman JG, et al (1985) Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. Opt Soc Amer, J A: Opt Image Sci 2(7):1160–1169

    Article  Google Scholar 

  8. Emerich S, Lup E, Belean B, Crisan S (2016) Image analysis and coding based on ordinal data representation. In: Image Feature Detectors and Descriptors. Springer-Verlag, Berlin, pp 281–303

    Chapter  Google Scholar 

  9. Gabor D (1946) Theory of communication. part 1: The analysis of information. J Inst of Electr Eng-Part III: Radio Commun Eng 93(26):429–441

    Google Scholar 

  10. Hachez G, Quisquater J-J, Koeune F (2000) Biometrics, access control, smart cards: a not so simple combination. In: Smart Card Research and Advanced Applications. Springer, Bristol, Inglaterra, pp 273–288

    Chapter  Google Scholar 

  11. Han C-C, Cheng H-L, Lin C-L, Fan K-C (2003) Personal authentication using palm-print features. Pattern Recogn 36(2):371–381

    Article  Google Scholar 

  12. Han Y, Tan T, Sun Z (2007) Palmprint recognition based on directional features and graph matching. In: Advances in Biometrics. Springer, Seoul, Coreia do Sul, pp 1164–1173

    Chapter  Google Scholar 

  13. Healthcare Council. Smart cards and biometrics in healthcare identity applications, 2012

  14. Hu D, Feng G, Zhou Z (2007) Two-dimensional locality preserving projections (2dlpp) with its application to palmprint recognition. Pattern Recogn 40(1):339–342

    Article  MATH  Google Scholar 

  15. Hubel DH, Wiesel TN (1977) Ferrier lecture: Functional architecture of macaque monkey visual cortex. Anais of the Royal Society of London. Series B, Biological Sciences, pp 1–59

  16. Jain AK, Chen Y, Demirkus M (2007) Pores and ridges: High-resolution fingerprint matching using level 3 features 29(1):15–27

  17. Jain AK, Feng J (2009) Latent palmprint matching. IEEE Trans Pattern Anal Mach Intell 31(6):1032–1047

    Article  Google Scholar 

  18. Jain AK, Ross A, Prabhakar S (2004) An introduction to biometric recognition. IEEE Trans Circ Syst Video Technol 14(1):4–20

    Article  Google Scholar 

  19. Jing X-Y, Tang Y-Y, Zhang D (2005) A fourier-lda approach for image recognition. Pattern Recogn 38(3):453–457

    Article  MATH  Google Scholar 

  20. Kittler J, Hatef M, Duin RPW, Matas J (1998) On combining classifiers. IEEE Trans Pattern Anal Mach Intell 20(3):226–239

    Article  Google Scholar 

  21. Kong A, Zhang D, Kamel M (2006) Palmprint identification using feature-level fusion. Pattern Recogn 39(3):478–487

    Article  MATH  Google Scholar 

  22. Kong AW-K, Zhang D (2004) Competitive coding scheme for palmprint verification. In: Anais. 17th International Conference on Pattern Recognition, 2004, vol 1. IEEE, Cambridge, Inglaterra, pp 520– 523

    Chapter  Google Scholar 

  23. Kumar A, Zhang D (2005) Personal authentication using multiple palmprint representation. Pattern Recogn 38(10):1695–1704

    Article  Google Scholar 

  24. Kumar A, Zhang D (2006) Personal recognition using hand shape and texture. IEEE Trans Image Process 15(8):2454–2461

    Article  Google Scholar 

  25. Li W, Zhang D, Xu Z (2002) Palmprint identification by fourier transform. Int J Pattern Recogn Artif Intell 16(04):417–432

    Article  Google Scholar 

  26. Li Y, Wang K, Zhang D (2005) Palmprint recognition based on translation invariant zernike moments and modular neural network, pp 177–182

  27. Lu G, Zhang D, Wang K (2003) Palmprint recognition using eigenpalms features. Pattern Recogn Lett 24(9):1463–1467

    Article  MATH  Google Scholar 

  28. PolyU (2013) Polyu 3d palmprint database, 2008 Acessado em fevereiro de

  29. Poon C, Wong DCM, Shen HC (2004) Personal identification and verification: fusion of palmprint representations. In: Biometric Authentication. Springer, Hong Kong, China, pp 782–788

    Chapter  Google Scholar 

  30. Pudzs M, Ruskuls RRF, Eglitis T, Kadikis A, Greitans M (2013) Fpga based palmprint and palm vein biometric system. In: Proceedings of IEEE International Conference on Biometrics Special Interest Group (BIOSIG)

  31. Shu W, Zhang D (1998) Automated personal identification by palmprint. Opt Eng 37(8):2359–2362

    Article  Google Scholar 

  32. Sun Z, Tan T, Wang Y, Li SZ (2005) Ordinal palmprint represention for personal identification representation. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), Washington, DC, USA, IEEE Computer Society, vol 1, pp 279–284

  33. Wang X, Gong H, Zhang H, Li B, Zhuang Z (2006) Palmprint identification using boosting local binary pattern. In: 18th International Conference on Pattern Recognition, 2006. ICPR 2006, vol 3. IEEE, Hong Kong, China, pp 503–506

    Google Scholar 

  34. Wei L, Zhang B, Lei Z, Yan J (2012) Principal line-based alignment refinement for palmprint recognition. IEEE Trans Syst, Man, Cybern, Part C 42(6):1491–1499

    Article  Google Scholar 

  35. Wu X, Wang K, Zhang D (2002) Fuzzy directional element energy feature (FDEEF) based palmprint identification. In: Proceedings of the 16th International Conference on Pattern Recognition, Québec City, QC, Canada, IEEE Computer Society, vol 1, pp 95–98

  36. Wu X, Zhang D, Wang K (2003) Fisherpalms based palmprint recognition. Pattern Recogn Lett 24(15):2829–2838

    Article  Google Scholar 

  37. Wu X, Zhang D, Wang K (2006) Fusion of phase and orientation information for palmprint authentication. Pattern Anal Appl 9(2-3):103–111

    Article  MathSciNet  Google Scholar 

  38. Wu X, Zhang D, Wang K (2006) Palm line extraction and matching for personal authentication. IEEE Trans Syst, Man Cybern Part A: Syst Humans 36(5):978–987

    Article  Google Scholar 

  39. Wyant RS, Nedjah N, De Macedo Mourelle L (2014) Efficient biometric palm-print matching on smart-cards. In: Computational Science and Its Applications - ICCSA 2014 - 14th International Conference. Proceedings, Part VI, Guimarães, Portugal, pp 236–247

    Google Scholar 

  40. Yang J, Zhang D, Yang J-Y, Niu B (2007) Globally maximizing, locally minimizing: unsupervised discriminant projection with applications to face and palm biometrics. IEEE Trans Pattern Anal Mach Intell 29(4):650–664

    Article  Google Scholar 

  41. You J, Kong W-K, Zhang D, Cheung KH (2004) On hierarchical palmprint coding with multiple features for personal identification in large databases. IEEE Trans Circ Syst Video Technol 14(2):234–243

    Article  Google Scholar 

  42. Zhang D, Kong W-K, You J, Wong M (2003) Online palmprint identification. IEEE Trans Pattern Anal Mach Intell 25(9):1041–1050

    Article  Google Scholar 

  43. Zhang D, Lu G, Li W, Zhang L, Luo N (2009) Palmprint recognition using 3-d information. IEEE Trans Syst, Man, Cybern, Part C: Appl Rev 39(5):505–519

    Article  Google Scholar 

  44. Zhang D, Zuo W, Yue F (2012) A comparative study of palmprint recognition algorithms. ACM Comput Surv (CSUR) 44(1):2

    Article  Google Scholar 

  45. Zuo W, Wang K, Zhang D (2005) Bi-directional pca with assembled matrix distance metric. In: IEEE International Conference on Image Processing, 2005. ICIP 2005, vol 2. IEEE, Genoa, Itlia, pp II– 958

    Google Scholar 

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Authors and Affiliations

  1. Department of Electronics Engineering and Telecommunications, Faculty of Engineering, State University of Rio de Janeiro, Rio de Janeiro, Brazil

    Nadia Nedjah & Rafael Soares Wyant

  2. Department of Systems Engineering and Computation, Faculty of Engineering, State University of Rio de Janeiro, Rio de Janeiro, Brazil

    Luiza de Macedo Mourelle

Authors
  1. Nadia Nedjah
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  2. Rafael Soares Wyant
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  3. Luiza de Macedo Mourelle
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Correspondence to Nadia Nedjah.

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Nedjah, N., Wyant, R.S. & de Macedo Mourelle, L. Efficient biometric palm-print matching on smart-cards for high security and privacy. Multimed Tools Appl 76, 22671–22701 (2017). https://doi.org/10.1007/s11042-016-4271-8

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  • DOI: https://doi.org/10.1007/s11042-016-4271-8

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