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アイテム
Biometric Authentication using Evoked EEG by Invisible Visual Stimulation - Feature Extraction Based on Wavelet Transform -
https://repository.lib.tottori-u.ac.jp/records/7039
https://repository.lib.tottori-u.ac.jp/records/70392f171ae0-c50a-434e-9e52-5c87fff4678b
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
SISA2019_88.pdf (673.5 kB)
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| Item type | 会議発表論文 / Conference Paper(1) | |||||||||||
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| 公開日 | 2020-06-05 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Biometric Authentication using Evoked EEG by Invisible Visual Stimulation - Feature Extraction Based on Wavelet Transform - | |||||||||||
| 言語 | en | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||
| 資源タイプ | conference paper | |||||||||||
| 著者 |
Kinjo, Nozomu
× Kinjo, Nozomu× Nakanishi, Isao
WEKO
2512
× Kinjo, Nozomu |
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| 著者所属（英） | ||||||||||||
| 言語 | en | |||||||||||
| 値 | Tottori University | |||||||||||
| 著者所属（英） | ||||||||||||
| 言語 | en | |||||||||||
| 値 | Tottori University | |||||||||||
| 抄録 | ||||||||||||
| 内容記述タイプ | Other | |||||||||||
| 内容記述 | In this study, we aim at the realization of authentication using evoked electroencephalogram (EEG) when presenting invisible visual stimulation as biometrics authentication towards safer and continuous authentication. In the previous researches, the measured EEG signal was processed by fast Fourier transform (FFT), and the power spectrum obtained was used as an individual feature, but the equal error rate (EER) representing the verification rate was about 43%. Therefore, in this paper, we introduce wavelet transform, which is a time-frequency analysis method, and extract a new individual feature including temporal information to improve the verification rate. As a result of evaluating the verification performance, in the case of presenting an invisible visual stimulation, the verification rate averaged over all electrodes tends to be improved as temporal information is included. In addition, as a result of evaluating the verification performance with data in which the start time of presenting stimulation is synchronized, the EER is the best at 14.0%, which is greatly improved compared to the conventional verification rate. | |||||||||||
| 書誌情報 |
Procedings of 2019 International Workshop on Smart Info-Media Systems in Asia (SISA 2019) en : Procedings of 2019 International Workshop on Smart Info-Media Systems in Asia (SISA 2019) p. 88-92, 発行日 2019 |
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| 出版者 | ||||||||||||
| 出版者 | 電子情報通信学会 = Institute of Electronics, Information and Communications Engineers (IEICE) | |||||||||||
| 権利 | ||||||||||||
| 権利情報 | ©2019 IEICE | |||||||||||
| 情報源 | ||||||||||||
| 関連名称 | Nozomu Kinjo, Isao Nakanishi. Biometric Authentication using Evoked EEG by Invisible Visual Stimulation - Feature Extraction Based on Wavelet Transform -. Procedings of 2019 International Workshop on Smart Info-Media Systems in Asia (SISA 2019), pp. 88-92 | |||||||||||
| 関連サイト | ||||||||||||
| 識別子タイプ | URI | |||||||||||
| 関連識別子 | https://search.ieice.org/ | |||||||||||
| 関連名称 | https://search.ieice.org/ | |||||||||||
| 著者版フラグ | ||||||||||||
| 出版タイプ | AM | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||
