In this paper, a person authentication system that can effectively identify individuals by generating unique electroencephalogram signal features in response to self-face and non-self-face photos is presented. In order to achieve a good stability performance, the sequence of self-face photo including first-occurrence position and non-first-occurrence position are taken into account in the serial occurrence of visual stimuli. In addition, a Fisher linear classification method and event-related potential technique for feature analysis is adapted to yield remarkably better outcomes than that by most of the existing methods in the field. The results have shown that the EEG-based person authentications via brain-computer interface can be considered as a suitable approach for biometric authentication system.
Al-HudhudG., AlzamelM.A., AlattasE. and AlwabilA., Using brain signals patterns for biometric identity verification systems, Computers in Human Behavior31 (2014), 224–229. doi:10.1016/j.chb.2013.09.018.
2.
BatistaL., GrangerE. and SabourinR., Dynamic selection of generative–discriminative ensembles for off-line signature verification, Pattern Recognition45 (2012), 1326–1340. doi:10.1016/j.patcog.2011.10.011.
3.
CaoK., YangX., ChenX., ZangY., LiangJ. and TianJ., A novel ant colony optimization algorithm for large-distorted fingerprint matching, Pattern Recognition45 (2012), 151–161. doi:10.1016/j.patcog.2011.04.016.
4.
CoburnK.L., ArrudaJ.E., EstesK.M. and AmossR.T., Diagnostic utility of visual evoked potential changes in Alzheimer's disease, The Journal of neuropsychiatry and clinical neurosciences15 (2003), 175–179. doi:10.1176/jnp.15.2.175.
5.
DellerJ.R.Jr., ProakisJ.G. and HansenJ.H., Discrete Time Processing of Speech Signals, Prentice Hall PTR, Upper Saddle River, NJ, USA, 1993.
6.
HuJ., EEG authentication system based on auto-regression coefficients, in: Intelligent Systems and Control (ISCO), IEEE, 2016, pp. 1–5.
7.
KimS., BanaschewskiT. and TannockR., Color vision in attention-deficit/hyperactivity disorder: A pilot visual evoked potential study, Journal of optometry8 (2015), 116–130. doi:10.1016/j.optom.2014.10.002.
8.
KumarR., SundararajanD., PonrajR.S. and SrinivasanM., A study on early detection of changes in visual pathway due to diabetes mellitus by visual evoked potential, International Journal of Medical Research & Health Sciences3 (2014), 161–164. doi:10.5958/j.2319-5886.3.1.031.
9.
MarcelS. and MillanJ., Person authentication using brainwaves (EEG) and maximum a posteriori model adaptation, IEEE Transactions on Pattern Analysis and Machine Intelligence29 (2007), 743–748. doi:10.1109/TPAMI.2007.1012.
10.
MiyamotoC., BabaS. and NakanishiI., Biometric person authentication using new spectral features of electroencephalogram (EEG), in: International Symposium on Intelligent Signal Processing and Communications Systems, IEEE, 2009, pp. 1–4.
11.
MukherjeeA., DeyG., DeyM. and DeyN., Web-based intelligent EEG signal authentication and tamper detection system for secure telemonitoring, in: Brain-Computer Interfaces, HassanienA.E. and AzarA.T., eds, Springer, Switzerland, 2015.
12.
PhamT., MaW., TranD., NguyenP. and PhungD., Multi-factor EEG-based user authentication, in: International Joint Conference on Neural Networks, IEEE, 2014, pp. 4029–4034.
13.
RankinD.M., ScotneyB.W., MorrowP.J. and PierscionekB.K., Iris Recognition Failure over Time: The Effects of Texture, Vol. 45, Pattern Recognition, 2012, pp. 145–150.
14.
TalebiM., MeshkinghalamA. and AndalibS., Association between visual evoked potential and disease severity, disease duration and visual hallucination in patients with idiopathic parkinsonism, Novelty in Biomedicine2 (2014), 120–125.
15.
YeomS.K., SukH.I. and LeeS.W., Person authentication from neural activity of face-specific visual self-representation, Pattern Recognition46 (2013), 1159–1169. doi:10.1016/j.patcog.2012.10.023.
16.
ZhangX., PhamD.S., VenkateshS., LiuW. and PhungD., Mixed-norm sparse representation for multi view face recognition, Pattern Recognition48 (2015), 2935–2946. doi:10.1016/j.patcog.2015.02.022.
