Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network
Fingerprints are known to be easily synthesized to trick identification systems. In this paper, we propose a new method that incorporates template fingerprints stored for identification in the liveness detection system. The fingerprint identification platform must have a list of template fingerprint...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8809706/ |
| _version_ | 1818323369156673536 |
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| author | Ho Yub Jung Yong Seok Heo Soochahn Lee |
| author_facet | Ho Yub Jung Yong Seok Heo Soochahn Lee |
| author_sort | Ho Yub Jung |
| collection | DOAJ |
| description | Fingerprints are known to be easily synthesized to trick identification systems. In this paper, we propose a new method that incorporates template fingerprints stored for identification in the liveness detection system. The fingerprint identification platform must have a list of template fingerprints stored for matching with new probe fingerprints trying to access the system. Thus, instead of simply detecting the liveness of the probe fingerprints, the proposed approach uses the matching template fingerprints along with probe fingerprints through convolutional neural networks to make the liveness decision, which comprises two sequential convolutional neural networks for classification. The proposed method can be built on the top of existing liveness detection methods to increase accuracy without a significant increase in computation time. The evaluation over the LivDet dataset shows that the proposed fingerprint liveness detection method is able to obtain state-of-the-art accuracy. |
| first_indexed | 2024-12-13T11:11:36Z |
| format | Article |
| id | doaj.art-bbc66fe9908e47e283c83ee7bed547ce |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T11:11:36Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-bbc66fe9908e47e283c83ee7bed547ce2022-12-21T23:48:44ZengIEEEIEEE Access2169-35362019-01-01711898611899310.1109/ACCESS.2019.29368908809706Fingerprint Liveness Detection by a Template-Probe Convolutional Neural NetworkHo Yub Jung0https://orcid.org/0000-0002-2906-9170Yong Seok Heo1https://orcid.org/0000-0001-7576-1347Soochahn Lee2https://orcid.org/0000-0002-2975-2519Department of Computer Engineering, Chosun University, Gwangju, South KoreaDepartment of Electrical and Computer Engineering, Ajou University, Suwon, South KoreaSchool of Electrical Engineering, Kookmin University, Seoul, South KoreaFingerprints are known to be easily synthesized to trick identification systems. In this paper, we propose a new method that incorporates template fingerprints stored for identification in the liveness detection system. The fingerprint identification platform must have a list of template fingerprints stored for matching with new probe fingerprints trying to access the system. Thus, instead of simply detecting the liveness of the probe fingerprints, the proposed approach uses the matching template fingerprints along with probe fingerprints through convolutional neural networks to make the liveness decision, which comprises two sequential convolutional neural networks for classification. The proposed method can be built on the top of existing liveness detection methods to increase accuracy without a significant increase in computation time. The evaluation over the LivDet dataset shows that the proposed fingerprint liveness detection method is able to obtain state-of-the-art accuracy.https://ieeexplore.ieee.org/document/8809706/Convolutional neural networkfingerprintsLivDetliveness detectionpretrainingtransfer learning |
| spellingShingle | Ho Yub Jung Yong Seok Heo Soochahn Lee Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network IEEE Access Convolutional neural network fingerprints LivDet liveness detection pretraining transfer learning |
| title | Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network |
| title_full | Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network |
| title_fullStr | Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network |
| title_full_unstemmed | Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network |
| title_short | Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network |
| title_sort | fingerprint liveness detection by a template probe convolutional neural network |
| topic | Convolutional neural network fingerprints LivDet liveness detection pretraining transfer learning |
| url | https://ieeexplore.ieee.org/document/8809706/ |
| work_keys_str_mv | AT hoyubjung fingerprintlivenessdetectionbyatemplateprobeconvolutionalneuralnetwork AT yongseokheo fingerprintlivenessdetectionbyatemplateprobeconvolutionalneuralnetwork AT soochahnlee fingerprintlivenessdetectionbyatemplateprobeconvolutionalneuralnetwork |