Research on EEG Identification Computing Based on Photo Images

Article Preview

Abstract:

In the information era, information security becomes more important, the use of EEG as identification tool become more and more. In this paper, we used the subjects’ photos as stimulation. In order to obtain the Identification classifier of different subjects, we used AR model to convert the EEG signals from time domain into the frequency domain, used Fisher’ distance to extract the feature. Finally, we calculated the feature by using BP neural network. Through the analysis of the correct recognition rate, error recognition rate and false recognition rate, we achieved the purpose of using EEG as identification tool.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 217-218)

Pages:

1366-1371

Citation:

Online since:

March 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Palaniappan R, Mandic D P. EEG Based Biometric Framework for Automatic Identity Verification. The Journal of VLSI Signal Processing, 2007, 49(2): 243-250.

DOI: 10.1007/s11265-007-0078-1

Google Scholar

[2] Palaniappan R. Method of identifying individuals using VEP signals and neural network. IEE Proceedings - Science, Measurement and Technology, 2004, 151(1): 16-20.

DOI: 10.1049/ip-smt:20040003

Google Scholar

[3] Palaniappan R. Electroencephalogram signals from imagined activities: a novel biometric identifier for a small population. Intelligent Data Engineering and Automated Learning (IDEAL), Lecture Notes in Computer Science 2006, 42: 604-611.

DOI: 10.1007/11875581_73

Google Scholar

[4] Touyama H, Hirose M. Non-target photo images in oddball paradigm improve EEG-based personal identification rates. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008, 1: 4118-21.

DOI: 10.1109/iembs.2008.4650115

Google Scholar

[5] Wardzinski R. Emerging biometrics: EEG-based identity verification. Proceedings of SPIE, the International Society for Optical Engineering, Photonics applications in astronomy, communications, industry, and high-energy physics experiments, 2006, 6347(2).

Google Scholar

[6] Poulos M, Rangoussi M, and Kafetzopoulos E, Person identification via the EEG using computational geometry algorithms. Proceedings of the 9th European Signal Processing (EUSIPCO '98), 1998, 2125–2128.

Google Scholar

[7] Poulos M, Rangoussi M, Chrissikopoulos V, et al. Parametric person identification from EEG using computational geometry. Proceedings of the 6th International Conference on Electronics, Circuits and Systems (ICECS '99), 1999, 2: 1005–1008.

DOI: 10.1109/icecs.1999.813403

Google Scholar

[8] Poulos M, Rangoussi M, Alexandris N, et al. On the use of EEG features towards person identification via neural networks. Medical Informatics & the Internet in Medicine, 2001, 26(1): 35–48.

DOI: 10.1080/14639230118937

Google Scholar

[9] Poulos M, Rangoussi M, Alexandris N, et al. Person identification from the EEG using nonlinear signal classification. Methods of Information in Medicine, 2002, 41(1): 64–75.

DOI: 10.1055/s-0038-1634316

Google Scholar

[10] Palaniappan R, Danilo P. Biometrics from Brain Electrical Activity: A Machine Learning Approach. IEEE transactions on pattern analysis and machine intelligence, 2007, 29(4): 738-742.

DOI: 10.1109/tpami.2007.1013

Google Scholar

[11] Ravi K V R, Palaniappan, R. Channel Set for Individual Identification with EEG Biometric Using Genetic Algorithm. Conference on Computational Intelligence and Multimedia Applications, 2007. 328-332.

DOI: 10.1109/iccima.2007.82

Google Scholar

[12] Ravi K V R, Palaniappan R, Eswaran C, et al. Data Encryption Using Event-related Brain Signals. Conference on Computational Intelligence and Multimedia Applications, 2007, 540-544.

DOI: 10.1109/iccima.2007.178

Google Scholar

[13] Gupta C N, Palaniappan R, Swaminathan S. Novel analysis technique for a brain biometric system. International Journal of Medical Engineering and Informatics, 2008, 1(2): 266 – 273.

DOI: 10.1504/ijmei.2008.020754

Google Scholar

[14] Ravi K V R, Palaniappan R. Recognising Individuals Using Their Brain Patterns, Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) , 2005, 2: 520 – 523.

DOI: 10.1109/icita.2005.234

Google Scholar

[15] Palaniappan R. Two-stage biometric authentication method using thought activity brain waves. International Journal of Neural Systems, 2008, 18(1): 59-66.

DOI: 10.1142/s0129065708001373

Google Scholar

[16] Ravi K V R, Palaniappan R. Leave-one-out Authentication of Persons Using 40 Hz EEG Oscillations Computer as a Tool. EUROCON, 2005, 1386-1389.

DOI: 10.1109/eurcon.2005.1630219

Google Scholar

[17] Nuri Fırat Ince, Sami Arica1 and Ahmed Tewfik. Classification of single trial motor imagery EEG recordings with subject adapted non-dyadi arbitrary time-frequency tilings. J. Neural Eng. 2006, 3: 235-244.

DOI: 10.1088/1741-2560/3/3/006

Google Scholar