Abstract
Sensitivity of global features to pose, illumination and scale variations encouraged researchers to use local features for object representation and recognition. Availability of 3D scanners also made the use of 3D data (which is less affected by such variations compared to its 2D counterpart) very popular in computer vision applications. In this paper, an approach is proposed for human ear recognition based on robust 3D local features. The features are constructed on distinctive locations in the 3D ear data with an approximated surface around them based on the neighborhood information. Correspondences are then established between gallery and probe features and the two data sets are aligned based on these correspondences. A minimal rectangular subset of the whole 3D ear data only containing the corresponding features is then passed to the Iterative Closest Point (ICP) algorithm for final recognition. Experiments were performed on the UND biometric database and the proposed system achieved 90, 94 and 96 percent recognition rate for rank one, two and three respectively. The approach is fully automatic, comparatively very fast and makes on assumption about the localization of the nose or the ear pit, unlike previous works on ear recognition.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Pun, K.H., Moon, Y.S.: Recent advances in ear biometrics. In: Proc. of the Sixth IEEE Int’l Conf. on Automatic Face and Gesture Recognition, pp. 164–169 (2004)
Islam, S., Bennamoun, M., Owens, R., Davies, R.: Biometric Approaches of 2D-3D Ear and Face: A Survey. In: Proc. of Int’l Conf. on Systems, Computing Sciences and Software Engineering, SCSS 2007 (2007)
Zhang, H.J., Mu, Z.C., Qu, W., Liu, L.M., Zhang, C.Y.: A novel approach for ear recognition based on ica and rbf network. In: Proc. of Int’l Conf. on Machine Learning and Cybernetics, 2005, pp. 4511–4515 (2005)
Hurley, D.J., Nixon, M.S., Carter, J.N.: Force field feature extraction for ear biometrics. Computer Vision and Image Understanding 98, 491–512 (2005)
Chang, K., Bowyer, K., Sarkar, S., Victor, B.: Comparison and combination of ear and face images in appearance-based biometrics. IEEE Transactions on Pattern Analysis and Machine Intelligence 9, 1160–1165 (2003)
Yan, P., Bowyer, K.W.: Biometric recognition using 3D ear shape. IEEE Trans. on PAMI 29, 1297–1308 (2007)
Yan, P., Bowyer, K.W.: An automatic 3D ear recognition system. In: Proc. of the Third Int’l Symposium on 3D Data Processing, Visualization and Transmission (2006)
Yan, P., Bowyer, K.W.: Icp-based approaches for 3d ear recognition. In: Jain, A.K., Ratha, N.K. (eds.) Biometric Technology for Human Identification II. Proc. of SPIE, vol. 5779, pp. 282–291 (2005)
Chen, H., Bhanu, B.: Contour matching for 3d ear recognition. In: Proc. of the 7th IEEE Workshops on Application of Computer Vision, pp. 123–128 (2005)
Yan, P., Bowyer, K.W.: Empirical evaluation of advanced ear biometrics. In: Proc. of Conf. on Empirical Evaluation Methods in Computer Vision (2005)
Choras, M.: Ear biometrics based on geometrical feature extraction. Electronic Letters on Computer Vision and Image Analysis 5, 84–95 (2005)
Yuizono, T., Wang, Y., Satoh, K., Nakayama, S.: Study on individual recognition for ear images by using genetic local search. In: Proc. of Congress on Evolutionary Computation, pp. 237–242 (2002)
Chen, H., Bhanu, B.: Human ear recognition in 3d. IEEE Trans. on PAMI 29, 718–737 (2007)
Mian, A., Bennamoun, M., Owens, R.: Keypoint Detection and Local Feature Matching for Textured 3D Face Recognition. International Journal of Computer Vision (IJCV) 79, 1–12 (2008)
Islam, S., Bennamoun, M., Davies, R.: Fast and Fully Automatic Ear Detection Using Cascaded AdaBoost. In: Proc. of IEEE Workshop on Application of Computer Vision WACV 2008, pp. 1–6 (2008)
Islam, S., Bennamoun, M., Mian, A., Davies, R.: A Fully Automatic Approach for Human Recognition from Profile Images Using 2D and 3D Ear Data. In: Proc. of the Fourth International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT 2008) (2008)
D’Errico, J.: Surface fitting using gridfit. MATLAB Central File Exchange Select (2006)
Besl, P.J., McKay, N.D.: A Method for Registration of 3-D Shapes. IEEE Trans. on PAMI 14, 239–256 (1992)
Mian, A., Bennamoun, M., Owens, R.: An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition. IEEE Trans. on PAMI 29, 1927–1943 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Islam, S.M.S., Davies, R., Mian, A.S., Bennamoun, M. (2008). A Fast and Fully Automatic Ear Recognition Approach Based on 3D Local Surface Features. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_98
Download citation
DOI: https://doi.org/10.1007/978-3-540-88458-3_98
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88457-6
Online ISBN: 978-3-540-88458-3
eBook Packages: Computer ScienceComputer Science (R0)