Personal identification based on acoustic characteristics of outer ear using cepstral analysis, Bayesian classifier, and artificial neural networks

Abstract

A hypothesis is discussed concerning the use of echograms of the external auditory canal for personal identification. The authors have developed a device for measuring the acoustic parameters of the external auditory canal. Obtained echograms can be used as biometric patterns for identification and authentication of subjects. Two types of biometric parameters are considered based on spectral and cepstral analyses of echograms. The authors used two approaches for recognizing ear patterns: the first was based on Bayes' formula and the second on artificial neural networks (convolutional and fully connected). The Bayesian classifier has been found to show a lower percentage of identification errors with an equal error rate (EER) = 0.0053. The best result for neural networks was EER = 0.0266. An experiment the authors repeated with the same subjects six months after the initial data collection showed insignificant deviation in the number of wrong decisions (EER = 0.008). | ACOUSTIC PROPERTIES AND STRUCTURE OF OUTER EARThe outer ear consists of the auricle and external auditory meatus, also called the auditory (ear) canal. This part of the ear is separated from the middle ear by the eardrum. The structure of the human ear is developed during childhood (up to 8 years); in adulthood, significant changes in the proportions of the ears and the channel do not occur [1]. The length, thickness, and, shape of the ear canal vary from person to person.The auricle and auditory canal are resonance systems. To obtain information about the internal structure of the This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Biometric-Based Key Generation and User Authentication Using Acoustic Characteristics of the Outer Ear and a Network of Correlation Neurons

“…A biometric authentication method based on an analysis of the acoustic properties of the ear canal was proposed in [ 1 ] and uses headphones with a built-in microphone. The headphones produce a sound signal that resonates in the ear canal.…”

“…These parameters can be “intercepted”, for example, fingerprints can be removed from door handles, mugs, and photographs and voices can be recorded on a dictaphone. The advantages of the method in [ 1 ] are that the characteristics of the auditory canal are hidden from direct observation and cannot be copied by being photographed. A “flat” ear image is not informative enough to make adversarial copies.…”

“…In the previously mentioned study [ 1 ], a set of impersonal (depersonalized) data of ear canal echograms of 75 computer users aged 18–40 years (AIC-ears-75) was collected, which is available for research purposes. Each echogram (or acoustic image of the auditory canal) is presented as a wav format file (mono, 44 kHz, 16 bit).…”

“…For the preliminary processing of the acoustic images of the auditory canal, the method of calculating the so-called averaged signal spectrum proposed in [ 1 ] was used. To obtain the averaged amplitude spectrum using a short-time Fourier transform, we first calculated the spectrogram with a window size W size = 65,536 (about one-and-a-half seconds of the signal according to [ 1 ]) and a step size W step = 16,384 (2 times less than that used in [ 1 ]). Further, for all windows, the spectrum of the average values of the amplitudes was calculated depending on the frequency ( Figure 11 a).…”

“…The effectiveness of the proposed model is illustrated by the example of the verification of a person by the peculiarities of the ear canal’s internal structure using an open data set of acoustic images (patterns) of ears (AIC-ears-75). The advantage of the ear canal features is that they are not compromised in the natural environment (a photograph of the ear is not informative and is not suitable for making a physical or digital fake of the ear for realizing adversarial attacks) [ 1 ]. This problem is difficult to solve because the parameters of the ear canal are significantly less informative than fingerprint and iris parameters.…”