Ear Recognition Using Texture Features - A Novel Approach

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 264)


Ear is a new class of relatively stable biometric that is invariant from childhood to old age. It is not affected with facial expressions, cosmetics and eye glasses. Human ear is one of the representative human biometrics with uniqueness and stability. Ear Recognition for Personal Identification using 2-D ear from a side face image is a challenging problem. This paper analyzes the efficiency of using texture features such as Gray Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP) and Gabor Filter for the recognition of ears. The combination of three feature vectors was experimented with. It is found that the combination gives better results compared to when the features were used in isolation. Further, it is found that the recognition accuracy improves by extracting local texture features extracted from sub-images. The proposed technique is tested using an ear database which contains 442 ear images of 221 subjects and obtained 94.12% recognition accuracy.


Ear recognition texture features co-occurrence matrix Local Binary Pattern Gabor Filter 


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  1. 1.
    Burge, M.: Ear Biometrics for Computer Vision. In: Proc. 21st Workshop Austrian Assoc. for Pattern Recognition, 1997, pp. 275–282 (2000)Google Scholar
  2. 2.
    Burge, W.: Burger: Using Ear Biometrics for Passive Identification. Published by Chapman & Hall. IP (1998)Google Scholar
  3. 3.
    Jitendra, B., Anjali, S.: Ear Based Attendance Monitoring System. In: Proceedings of ICETECT (2011)Google Scholar
  4. 4.
    Meijerman, L., Thean, A., Maat, G.J.R.: Earprints In Forensic Investigations. Forensic Science, Medicine and Pathology 1(4), 247–256 (2005)CrossRefGoogle Scholar
  5. 5.
    Guo, Y., Xu, Z.: Ear recognition using a new local matching approach. In: Image Processing, ICIP 2008, pp. 289–292 (2008)Google Scholar
  6. 6.
    Pug, A., Busch, C.: Ear Biometrics - A Survey of Detection, Feature Extraction and Recognition Methods. IET Biometrics Journal 1(2), 114–129 (2012) ISSN 2047-4938Google Scholar
  7. 7.
    Lu, L., Xiaoxun, Z., Youdong, Z., Yunde, J.: Ear Recognition Based on Statistical Shape Model. CICIC (3), 353–356 (2006)Google Scholar
  8. 8.
    Hurley, D.J., Nixon, M.S., Carter, J.N.: Force Field Feature Extraction for Ear Biometrics. Computer Vision and Image Understanding, 491–512 (June 2005)Google Scholar
  9. 9.
    Moreno, B., Sanchez, A., Velez, J.F.: On the use of outer ear images for personal identification in security applications. In: Proceedings of IEEE Conference on Security Technology, pp. 469–476 (1999)Google Scholar
  10. 10.
    Kumar, A., Wu, C.: Automated human identification using ear imaging. Pattern Recognition 45(3), 956–968Google Scholar
  11. 11.
    Takala, V., Ahonen, T., Pietikäinen, M.: Block-Based Methods for Image Retrieval Using Local Binary Patterns. In: Proc. 14th Scandinavian Conference, SCIA, pp. 882–891 (2005)Google Scholar
  12. 12.
    Wang, Y., Mu, Z.-C., Zeng, H.: Block-based and Multi-resolution Methods for Ear Recognition Using Wavelet Transform and Uniform Local Binary Patterns. In: Pattern Recognition, ICPR 2008, pp. 1–4 (2008)Google Scholar
  13. 13.
    Xiaoyun, W., Weiqi, Y.: Human Ear Recognition Based on Block Segmentation Cyber-Enabled Distributed Computing and Knowledge Discovery, pp. 262–266 (2009)Google Scholar
  14. 14.
    Jawale, S.: Wavelet Transform and Co-occurance matrix based texture features for CBIR. International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622Google Scholar
  15. 15.
    Ahonen, T., Hadid, A., Pietikanen, M.: Face Description with Local Binary Patterns: Application to Face Recognition. IEEE, IEEE Transactions on Pattern Analysis And Machine Intelligence 28(12) (December 2006)Google Scholar
  16. 16.
    Haralick, R.M., Shanmugam, K., Dinstein, I.: Textural Features for Image Classification. IEEE Transactions on Systems, Man and Cybernetics SMC-3(6), 610–621 (1973)CrossRefGoogle Scholar
  17. 17.
    Manjunath, B., Ma, W.: Texture features for browsing and retrieval of image data. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(8), 837–842 (1996)CrossRefGoogle Scholar
  18. 18.
    Mäenpää, T., Pietikäinen, M.: Texture Analysis with Local Binary Patterns. In: Chen, C.H., Wang, P.S.P. (eds.) Handbook of Pattern Recognition and Computer Vision, 3rd edn., pp. 197–216. World Scientific (2005)Google Scholar
  19. 19.
    Ross, A., Jain, A.K.: Multimodal Biometrics: an overview. In: Proceedings of the European Signal Processing Conference, pp. 1221–1224 (2004)Google Scholar
  20. 20.
    Cadavid, S., Mahoor, M.H., Abdel-Mottaleb, M.: Multi-modal Biometric Modeling and Recognition of the Human Face and Ear. Cambridge University Press (2011)Google Scholar
  21. 21.
    Yuan, L., Mu, Z.-C.: Multimodal recognition using ear and face. In: 5th International Conference on Wavelet Analysis and Pattern Recognition, Beijing (2007)Google Scholar
  22. 22.
    Deniz, O., Bueno, G., Salido, J., De la Torre, F.: Face Recognition using Histogram of Oriented Gradients. Pattern Recognition Letters 32(12) (September 1, 2011)Google Scholar
  23. 23.
    Maenpaa, T., Pietikainen, M.: Texture Analysis with local binary patternsGoogle Scholar
  24. 24.
    Hammouda, K., Jernigan, E.: Texture Segmentation Using Gabor Filters, University of Waterloo, Ontario, CanadaGoogle Scholar
  25. 25.
    Choras, M.: Ear Biometrics based on Geometrical Feature Extraction. Electronic Letters on Computer Vision and Image Analysis 5(3), 84–95 (2005)Google Scholar
  26. 26.
    Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray scale and rotation invariant texture analysis with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 971–987 (2002)CrossRefGoogle Scholar
  27. 27.
    Movellan, J.: Tutorial on Gabor Filters, Technical report, MPLab Tutorials, Univ. of California, San Diego (2005)Google Scholar
  28. 28.
    Shailaja, D., Gupta, P.: A Simple Geometric Approach for Ear Recognition. In: 9th International Conference on Information Technology (ICIT 2006) (2006)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Saintgits College of EngineeringKottayamIndia
  2. 2.Department of Information TechnologyKannur UniversityKannurIndia

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