Abstract
This work concerns the use of biometric features, resulting from the look of a face, for the authentication purposes. For this we propose several different methods of selection and feature analysis during face recognition. The description contains mainly the possibility of the analysis and in later stages also identity verification based on asymmetric facial features. The new authentication method has been introduced on the basis of designated characteristic points of face. The method includes propositions of our own algorithms of face detection, as well as face features extraction methods and their specific coding in the form of observation vectors and recognition using Hidden Markov Models.
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Kubanek, M., Smorawa, D., Kurkowski, M. (2014). Using Facial Asymmetry Properties and Hidden Markov Models for Biometric Authentication in Security Systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_55
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DOI: https://doi.org/10.1007/978-3-319-07176-3_55
Publisher Name: Springer, Cham
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