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Evaluation of Acceleration Algorithm for Biometric Identification

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Networked Digital Technologies (NDT 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 294))

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Abstract

This paper evaluates an existing acceleration algorithm for biometric identification. In identification based on biometric images, the number of image comparisons is an important factor to estimate the total processing time in addition to the processing time of a single image comparison. Maeda et al. proposed an identification algorithm which reduces the number of image comparisons. This paper evaluates the algorithm in terms of the time and the accuracy with the features extracted by SIFT from palmprint images. The evaluation in this paper proves that the algorithm is applicable to the SIFT-based palmprint features. However, the evaluation also proves that an overhead of the algorithm requires the processing time which depends on the database size. Therefore, for an identification system with a large database, the total processing time of an identification is not reduced by a straightforward application of the algorithm by Maeda et al.

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References

  1. OpenCV, http://opencv.willowgarage.com/wiki/

  2. PolyU Palmprint Database, http://www4.comp.polyu.edu.hk/~biometrics/

  3. Chen, J., Moon, Y.-S.: Using SIFT features in palmprint authentication. In: Proc. 19th International Conference on Pattern Recognition, pp. 1–4. IEEE (2008)

    Google Scholar 

  4. Friedman, J.H., Bentley, J.L., Finkel, R.A.: An algorithm for finding best matches in logarithmic expected time. ACM Trans. Math. Softw. 3, 209–226 (1977)

    Article  MATH  Google Scholar 

  5. Iannizzotto, G., Rosa, F.L.: A SIFT-based fingerprint verification system using cellular neural networks. In: Pattern Recognition Techniques, Technology and Applications, pp. 523–536. InTech (2008)

    Google Scholar 

  6. Indyk, P., Motwani, R.: Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the Thirtieth Annual ACM Symposium on Theory of Computing, STOC 1998, pp. 604–613. ACM, New York (1998)

    Chapter  Google Scholar 

  7. Jain, A.K., Ross, A.A., Nandakumar, K.: Introduction to Biometrics. Springer (2011)

    Google Scholar 

  8. Kong, A., Zhang, D., Kamel, M.: A Survey of Palmprint Recognition. Pattern Recogn. 42, 1408–1418 (2009)

    Article  Google Scholar 

  9. Lowe, D.G.: Object recognition from local scale-invariant features. In: Proc. IEEE International Conference on Computer Vision, pp. 1150–1157 (1999)

    Google Scholar 

  10. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)

    Article  Google Scholar 

  11. Maeda, T., Matsushita, M., Sasakawa, K.: Identification algorithm using a matching score matrix. IEICE Transactions on Information and Systems E84-D(7), 819–824 (2001)

    Google Scholar 

  12. Morales, A., Ferrer, M.A., Kumar, A.: Improved palmprint authentication using contactless imaging. In: Proc. IEEE Fourth International Conference on Biometrics: Theory Applications and Systems, pp. 1–6. IEEE (2010)

    Google Scholar 

  13. Park, U., Pankanti, S., Jain, A.K.: Fingerprint verification using SIFT features. In: Proc. SPIE Defense and Security Symposium (2008)

    Google Scholar 

  14. Zhang, D., Kong, W.-K., You, J., Wong, M.: Online palmprint identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(9), 1041–1050 (2003)

    Article  Google Scholar 

  15. Zhang, D.D.: Palmprint Authentication. Kluwer Academic Publishers (2004)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Egawa, S., Awad, A.I., Baba, K. (2012). Evaluation of Acceleration Algorithm for Biometric Identification. In: Benlamri, R. (eds) Networked Digital Technologies. NDT 2012. Communications in Computer and Information Science, vol 294. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30567-2_19

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  • DOI: https://doi.org/10.1007/978-3-642-30567-2_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30566-5

  • Online ISBN: 978-3-642-30567-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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