TY - GEN
T1 - Improving individual identification in security check with an EEG based biometric solution
AU - Zhao, Qinglin
AU - Peng, Hong
AU - Hu, Bin
AU - Liu, Quanying
AU - Liu, Li
AU - Qi, Yan Bing
AU - Li, Lanlan
PY - 2010
Y1 - 2010
N2 - Security issue is always challenging to the real world applications. Many biometric approaches, such as fingerprint, iris and retina, have been proposed to improve recognizing accuracy or practical facility in individual identification in security. However, there is little research on individual identification using EEG methodology mainly because of the complexity of EEG signal collection and analysis in practice. In this paper, we present an EEG based unobtrusive and non-replicable solution to achieve more practical and accurate in individual identification, and our experiment involving 10 subjects has been conducted to verify this method. The accuracy of 10 subjects can reach at 96.77%. The high-level accuracy result has validated the utility of our solution in the real world. Besides, subject combinations were randomly selected, and the recognizing performance from 3 subjects to 10 subjects can still keep equivalent, which has proven the extendibility of the solution.
AB - Security issue is always challenging to the real world applications. Many biometric approaches, such as fingerprint, iris and retina, have been proposed to improve recognizing accuracy or practical facility in individual identification in security. However, there is little research on individual identification using EEG methodology mainly because of the complexity of EEG signal collection and analysis in practice. In this paper, we present an EEG based unobtrusive and non-replicable solution to achieve more practical and accurate in individual identification, and our experiment involving 10 subjects has been conducted to verify this method. The accuracy of 10 subjects can reach at 96.77%. The high-level accuracy result has validated the utility of our solution in the real world. Besides, subject combinations were randomly selected, and the recognizing performance from 3 subjects to 10 subjects can still keep equivalent, which has proven the extendibility of the solution.
KW - EEG
KW - Security check
KW - individual identification
UR - https://www.scopus.com/pages/publications/78249244777
U2 - 10.1007/978-3-642-15314-3_14
DO - 10.1007/978-3-642-15314-3_14
M3 - Conference contribution
AN - SCOPUS:78249244777
SN - 3642153135
SN - 9783642153136
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 145
EP - 155
BT - Brain Informatics - International Conference, BI 2010, Proceedings
T2 - 2010 International Conference on Brain Informatics, BI 2010
Y2 - 28 August 2010 through 30 August 2010
ER -