Abstract
This paper proposes a faces verification in which the feature extraction is carried out using the discrete Gabor function (DGF), while the Gaussian Mixture Model (GMM) is used in the face verification stage. Evaluation results using standard data bases with different parameters, such as the number of mixtures and the number of face used for training show that proposed system provides better results that other proposed systems with a correct verification rate larger than 95%. Although, as happens in must face recognition systems, the verification rate decreases when the target faces present some rotation degrees.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Reid, P.: BIOMETRICS for Networks Security, pp. 3–7. Prentice Hall, New Jersey (2004)
Chellappa, R., Wilson, C., Sirohey, S.: Human and Machine Recognition of Faces: A Survey. Proc. IEEE 83(5), 705–740 (1995)
Shashua, A.: Geometry and Photometry in 3D Visual Recognition. PhD thesis, Massachusetts Institute of Technology (1992)
Baron. R.J.: Mechanisms of human facial recognition. International Journal of Man-Machine Studies, 137–178 (1981)
Dunn, D., Higgins, W.E.: Optimal Gabor Filters for Texture Segmentation. In: IEEE Trans. Image Proc 4(7) (July 1995)
Kim, J.Y., Ko, D.Y., Na., S.Y.: Implementation and Enhancement of GMM Face Recognition Systems Using Flatness Measure. IEEE Robot and Human Interactive Communication (September 2004)
Reynolds, D.A., Rose, R.C.: Robust Text-Independent Speaker Identification Using Gaussian Mixture Speaker Models. IEEE Trans. Speech and audio Proc 3(1) (January 1995)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Olivares-Mercado, J., Sanchez-Perez, G., Nakano-Miyatake, M., Perez-Meana, H. (2007). Feature Extraction and Face Verification Using Gabor and Gaussian Mixture Models. In: Gelbukh, A., Kuri Morales, Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science(), vol 4827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76631-5_73
Download citation
DOI: https://doi.org/10.1007/978-3-540-76631-5_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76630-8
Online ISBN: 978-3-540-76631-5
eBook Packages: Computer ScienceComputer Science (R0)