Идентификация личности на основе индивидуальных эхографических свойств ушной раковины с использованием кепстрального анализа и формулы Байеса / Сулавко А. Е., Ложников П. С., Куприк И. А., Самотуга А. Е. (2021)
Ukrainian

English  Cybernetics and Systems Analysis   /     Issue (2021, 57 (3))

Sulavko A.E., Lozhnikov P.S., Kuprik I.A., Samotuga A.E.
Personal identification based on the individual sonographic properties of the auricle using cepstral analysis and bayes formula

A method of personality recognition by echographic parameters of the human ear is developed based on the naive Bayes classifier in the two following modes: the biometric identification (EER = 0.0053) and the biometric authentication (FRR = 0.0002 at FAR ≤ 0.0001), respectively. A device is developed for recording the biometric characteristics of the external ear, and a set of echographic data is collected from the external ears of 75 subjects. The spectral and cepstral characteristics of the signals reflected from the ear canal are used as biometric parameters. Several window functions for constructing spectra and cepstrograms are considered. It is established that more than 90% of “cepstral” features have a weak correlation, which allows us to use the naive Bayesian classifier and to obtain highly accurate results of user recognition at the same time. An advantage of the Bayesian classification is the possibility of the robust fast learning of the identification system. © 2021, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: acoustic signal, Bayes theorem, cepstrograms, machine learning, pattern recognition, windowed Fourier transform, Biometrics, Classifiers, Bayesian classification, Biometric authentication, Biometric identifications, Biometric parameters, Naive Bayes classifiers, Naive Bayesian Classifier, Personal identification, Personality recognition, Learning systems


Cite:
Sulavko A.E., Lozhnikov P.S., Kuprik I.A., Samotuga A.E. (2021). Personal identification based on the individual sonographic properties of the auricle using cepstral analysis and bayes formula. Cybernetics and Systems Analysis, 57 (3), 135–143. doi: https://doi.org/10.1007/s10559-021-00370-w http://jnas.nbuv.gov.ua/article/UJRN-0001239415 [In Russian].


 

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