Abstract
In this paper, we propose a novel face authentication approach based on affine scale invariant feature transform (ASIFT) and structural similarity (SSIM). The ASIFT descriptor defines key points which are used to match the gallery and probe face images. The matched pairs of key points are filtered based on the location of points in the gallery face image. Then the similarity between sub-images at a preserved pair of matched points is measured by Structural Similarity (SSIM). A mean SSIM (MSSIM) at all pairs of points is computed for authentication. The proposed approach is tested on FERET, CMU-PIE and AR databases with only one image for enrollment. Comparative results on the AR database show that our approach outperforms state-of-the-art approaches.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Struc, V., Gajsek, R., Pavesic, N.: Principal gabor filters for face recognition. In: IEEE Third International Conference on Biometrics: Theory, Applications and Systems (BTAS), Washington, DC, USA (2009)
Lowe, D.G.: Object recognition from local scale-invariant features. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 1150–1157 (1999)
Bicego, M., Lagorio, A., Grosso, E., Tistarelli, M.: On the use of SIFT features for face authentication. In: Proc. of IEEE Int. Workshop on Biometrics, in Association with CVPR, p. 35 (2006)
Kisku, D., Rattani, A., Grosso, E., Tistarelli, M.: Face identification by SIFT-based complete graph topology. In: IEEE Workshop on Automatic Identification Advanced Technologies, pp. 63–68 (2007)
Rosenberger, C., Brun, L.: Similarity-based matching for face authentication. In: International Conference on Pattern Recognition, ICPR (2008)
Martinez, A., Benavente, R.: The AR face database. CVC Tech. Report 24 (1998)
Hemery, B., Schwartzmann, J.J., Rosenberger, C.: Study on Color Spaces for Single Image Enrollment Face Authentication. In: International Conference on Pattern Recognition (ICPR), pp. 1249–1252 (2010)
Liao, S., Jain, A.: Partial Face Recognition: An Alignment Free Approach. In: Proc. 2011 IEEE International Joint Conference on Biometrics, pp. 1–8 (2011)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error visibility to structural similarity. IEEE Transaction on Image Processing, 600–612 (2004)
Yu, G., Morel, J.-M.: A fully affine invariant image comparison method. In: ICASSP, pp. 1597–1600 (2009)
Phillips, P., Wechsler, H., Huang, J., Rauss, P.: The feret database and evaluation procedure for face recognition algorithms. Journal of Image and Vision Computing 16(5), 295–306 (1998)
Sim, T., Baker, S.: The CMU Pose, Illumination Expression Database. IEEE PAMI 25(12) (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, L., Zhou, P., Liu, S., Zhang, X., Trucco, E. (2012). A Face Authentication Scheme Based on Affine-SIFT (ASIFT) and Structural Similarity (SSIM). In: Zheng, WS., Sun, Z., Wang, Y., Chen, X., Yuen, P.C., Lai, J. (eds) Biometric Recognition. CCBR 2012. Lecture Notes in Computer Science, vol 7701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35136-5_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-35136-5_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35135-8
Online ISBN: 978-3-642-35136-5
eBook Packages: Computer ScienceComputer Science (R0)