Abstract
We have previously described how force field feature extraction can be used to exploit the directional properties of a force field generated from an ear image to automatically locate potential wells and channels which then form the basis of characteristic ear features. We now show how an analysis of the mechanism of this algorithmic field line approach leads to an additional closed analytical description based on the divergence of force direction revealing even more information in the form of anti-wells and anti-channels. In addition to furnishing specific implementation details for much faster FFT based computation and demonstrating brightness insensitivity, the technique is validated by achieving a recognition rate of 99.2% on a set of 252 ear images taken from the XM2VTS face database. These results demonstrate the inherent automatic extraction advantage of the new technique, especially when compared with more traditional PCA where we show that the ear set has to be more accurately extracted and registered in order to achieve comparable results. We show that it performs even more favourably against PCA under variable brightness conditions, and we also demonstrate its excellent noise performance by showing that noise has little effect on recognition results. Thus we have introduced a powerful new extension to complement our existing technique and we have validated it by achieving good ear recognition results, and in the process we have contributed to the mounting evidence that the human ear has considerable biometric value.
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Burge, M., Burger, W.: Ear biometrics in computer vision. In: Proc. ICPR 2000, pp. 822–826 (2002)
Chang, K., Bowyer, K.W., Sarkar, S., Victor, B.: Comparison and Combination of Ear and Face Images in Appearance-Based Biometrics. IEEE Trans. PAMI 25(9), 1160–1165 (2003)
Moreno, B., Sanchez, A., Velez, J.F.: On the Use of Outer Ear Images for Personal Identification in Security Applications. In: Proc. IEEE 33rd Annual International Carnahan Conference on Security Technology, October 5-7 (1999)
Bhanu, B., Chen, H.: Human Ear Recognition in 3D. In: Workshop on Multimodal User Authentication, Santa Barbara, CA, December 2003, pp. 91–98 (2003)
Iannarelli, A.: Ear Identification. Paramount Publishing Company, Freemont (1989)
STATE v. David Wayne KUNZE, Court of Appeals of Washington, Division 2. 97 Wash. App. 832, 988 P.2d 977 (1999)
Mark Dallagher Released, News item: The Chambers of William Clegg QC (January 28, 2004),available from www.2bedfordrow.co.uk/NewsDetail.asp?NewsID=17
Hurley, D.J., Nixon, M.S., Carter, J.N.: Force Field Energy Functionals for Image Feature Extraction. In: Proc. 10th British Machine Vision Conference BMVC 1999, pp. 604–613 (1999)
Hurley, D.J., Nixon, M.S., Carter, J.N.: Force Field Energy Functionals for Image Feature Extraction. Image and Vision Computing 20, 311–317 (2002)
Hurley, D.J., Nixon, M.S., Carter, J.N.: A New Force Field Transform for Ear and Face Recognition. In: Proceedings IEEE International Conference on Image Processing ICIP 2000, pp. 25–28 (2000)
Hurley, D.J., Nixon, M.S., Carter, J.N.: Force Field Feature Extraction for Ear Biometrics. Computer Vision and Image Understanding (2005) (in press)
Luo, B., Cross, A.D., Hancock, E.R.: Corner Detection Via Topographic Analysis of Vector Potential. Pattern Recognition Letters 20(6), 635–650 (1999)
Ahuja, N.: A Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection. IEEE Transactions on PAMI 18(12), 1211–1235 (1996)
Xu, C., Prince, J.L.: Gradient Vector Flow: A New External Force for Snakes. In: Proc. IEEE Conf. on Comp. Vis. Patt. Recog (CVPR), pp. 66–71 (1997)
Messer, K., Matas, J., Kittler, J., Luettin, J., Maitre, G.: XM2VTSDB: The Extended M2VTS Database. In: Proc. AVBPA 1999, Washington, D.C (1999)
Sadiku, M.N.O.: Elements of Electromagnetics, 2nd edn. Saunders College Publishing, Philadelphia (1989)
Daugman, J.: Biometric decision landscapes, Technical Report TR482, University of Cambridge Computer Laboratory (1999)
Turk, M., Pentland, A.: Eigenfaces for Recognition. Journal of Cognitive Neuroscience, 71–86 (March 1991)
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© 2005 Springer-Verlag Berlin Heidelberg
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Hurley, D.J., Nixon, M.S., Carter, J.N. (2005). Ear Biometrics by Force Field Convergence. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_40
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DOI: https://doi.org/10.1007/11527923_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27887-0
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