Integration of statistical method and zernike moment as feature extraction in liveness detection
Recently, fake fingerprints have been used to defeat fingerprint recognition systems. These fake fingerprints are created without the need for any expertise and use easily found materials. In this paper, a fake fingerprint detection method is proposed that employs a combination of eleven statistical...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/90180/1/AsrafulSyifaaAhmad2019_IntegrationofStatisticalMethod.pdf http://eprints.utm.my/id/eprint/90180/ https://dx.doi.org/10.1088/1757-899X/551/1/012064 |
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| Summary: | Recently, fake fingerprints have been used to defeat fingerprint recognition systems. These fake fingerprints are created without the need for any expertise and use easily found materials. In this paper, a fake fingerprint detection method is proposed that employs a combination of eleven statistical methods and integrating them with Zernike Moment as the feature extractor. Based on the experimental results, the proposed method showed average classification accuracy, sensitivity and specificity of approximately 80% for all sensors used to capture fake fingerprint images fabricated by gelatine and latex materials. |
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