An Efficient 3D Ear Recognition System Based on Indexing

  • Qinping Zhu
  • Zhichun MuEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)


We propose a system for time-efficient 3D ear biometrics. The system is composed of two primary components, namely: (1) an ear shape-based index; and (2) categorization using the index. We built an index tree by using the shape feature computed from measures of circularity, rectangularity, ellipticity, and triangularity, based on ear segmentation results and then perform a nearest neighbor search to obtain a gallery of ear images that are closest in shape to the probe subjects. For the categorization component, separate index trees are built out of the gallery of ear images by using a reduced depth feature space for each image. We utilize an indexing technique to perform a range query in a reduced depth feature space for ears that are closest in shape to the probe subject. Experiments on the benchmark database demonstrate that the proposed approach is more efficient compared to the state-of-the-art 3D ear biometric system.


Ear biometrics 3D ear segmentation 3D ear database categorization Indexing KD tree Pyramid technique 


  1. 1.
    Sun, X., Wang, G., Wang, L., Sun, H., Wei, X.: 3D ear recognition using local salience and principal manifold. Graph. Models 76(5), 402–412 (2014)CrossRefGoogle Scholar
  2. 2.
    Yan, P., Bowyer, K.W.: Biometric recognition using 3D ear shape. IEEE Trans. Pattern Anal. Mach. Intell. 29(8), 1297–1308 (2007)CrossRefGoogle Scholar
  3. 3.
    Chen, H., Bhanu, B.: Contour matching for 3-D ear recognition. In: Proceedings of IEEE Workshop on Applications Computer Vision, January, pp. 123–128 (2005)Google Scholar
  4. 4.
    Chen, H., Bhanu, B.: Human ear recognition in 3D. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 718–737 (2007)Google Scholar
  5. 5.
    Zhou, J., Cadavid, S., Abdel-Mottaleb, M.: A computationally efficient approach to 3D ear recognition employing local and holistic features. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 98–105 (2011)Google Scholar
  6. 6.
    Zhou, J., Cadavid, S., Abdel-Mottaleb, M.: An efficient 3-D ear recognition system employing local and holistic features. IEEE Trans. Inf. Forensics Secur. 7(3), 978–991 (2012)Google Scholar
  7. 7.
    Maity, S., Abdel-Mottable, M.: 3D segmentation and classification through indexing. IEEE Trans. Inf. Forensics Secur. 10(2), 423–435 (2015)Google Scholar
  8. 8.
    Lei, J., Zhou, J., Abdel-Mottaleb, M., You, X.: Detection, localization and pose classification of ear in 3D face profile images. In: Proceedings of 20th IEEE International Conference on Image Processing, pp. 4200–4204 (2013)Google Scholar
  9. 9.
    Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. Int. J. Comput. Vis. 1(4), 321–331 (1988)Google Scholar
  10. 10.
    Bentley, J.L.: Multidimensional binary search trees used for associative searching. Commun. ACM 18(9), 509–517 (1975)Google Scholar
  11. 11.
    Žunić, J., Hirota, K., Rosin, P.L.: A Hu moment invariant as a shape circularity measure. Pattern Recognit. 43(1), 47–57 (2010)Google Scholar
  12. 12.
    Rosin, P.L.: Measuring rectangularity. Mach. Vis. Appl. 11(4), 191–196 (1999)Google Scholar
  13. 13.
    Rosin, P.: Measuring shape: ellipticity, rectangularity, and triangularity. Mach. Vis. Appl. 14(3), 172–184 (2003)Google Scholar
  14. 14.
    Jolliffe, I.: Principal Component Analysis. Wiley, Hoboken (2005)CrossRefGoogle Scholar
  15. 15.
    Berchtold, S., Böhm, C., Kriegal, H.-P.: The pyramid-technique: towards breaking the curse of dimensionality. ACM SIGMOD Rec. 27(2), 142–153 (1998)Google Scholar
  16. 16.
    Battiato, S., Cantone, D., Catalano, D., Cincotti, G., Hofri, M.: An efficient algorithm for the approximate median selection problem. In: Bongiovanni, G., Petreschi, R., Gambosi, G. (eds.) CIAC 2000. LNCS, vol. 1767, pp. 226–238. Springer, Heidelberg (2000). Scholar
  17. 17.
    Prakash, S., Gupta, P.: Human recognition using 3D ear images. Neurocomputing 140, 317–325 (2014)Google Scholar

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Authors and Affiliations

  1. 1.School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijingChina

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