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A Smart Spoofing Face Detector by Display Features Analysis
In this paper, a smart face liveness detector is proposed to prevent the biometric system from being “deceived” by the video or picture of a valid user that the counterfeiter took with a high definition handheld device (e.g., iPad with retina display). By analyzing the characteristics of the display...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970178/ https://www.ncbi.nlm.nih.gov/pubmed/27455259 http://dx.doi.org/10.3390/s16071136 |
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author | Lai, ChinLun Tai, ChiuYuan |
author_facet | Lai, ChinLun Tai, ChiuYuan |
author_sort | Lai, ChinLun |
collection | PubMed |
description | In this paper, a smart face liveness detector is proposed to prevent the biometric system from being “deceived” by the video or picture of a valid user that the counterfeiter took with a high definition handheld device (e.g., iPad with retina display). By analyzing the characteristics of the display platform and using an expert decision-making core, we can effectively detect whether a spoofing action comes from a fake face displayed in the high definition display by verifying the chromaticity regions in the captured face. That is, a live or spoof face can be distinguished precisely by the designed optical image sensor. To sum up, by the proposed method/system, a normal optical image sensor can be upgraded to a powerful version to detect the spoofing actions. The experimental results prove that the proposed detection system can achieve very high detection rate compared to the existing methods and thus be practical to implement directly in the authentication systems. |
format | Online Article Text |
id | pubmed-4970178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-49701782016-08-04 A Smart Spoofing Face Detector by Display Features Analysis Lai, ChinLun Tai, ChiuYuan Sensors (Basel) Article In this paper, a smart face liveness detector is proposed to prevent the biometric system from being “deceived” by the video or picture of a valid user that the counterfeiter took with a high definition handheld device (e.g., iPad with retina display). By analyzing the characteristics of the display platform and using an expert decision-making core, we can effectively detect whether a spoofing action comes from a fake face displayed in the high definition display by verifying the chromaticity regions in the captured face. That is, a live or spoof face can be distinguished precisely by the designed optical image sensor. To sum up, by the proposed method/system, a normal optical image sensor can be upgraded to a powerful version to detect the spoofing actions. The experimental results prove that the proposed detection system can achieve very high detection rate compared to the existing methods and thus be practical to implement directly in the authentication systems. MDPI 2016-07-21 /pmc/articles/PMC4970178/ /pubmed/27455259 http://dx.doi.org/10.3390/s16071136 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lai, ChinLun Tai, ChiuYuan A Smart Spoofing Face Detector by Display Features Analysis |
title | A Smart Spoofing Face Detector by Display Features Analysis |
title_full | A Smart Spoofing Face Detector by Display Features Analysis |
title_fullStr | A Smart Spoofing Face Detector by Display Features Analysis |
title_full_unstemmed | A Smart Spoofing Face Detector by Display Features Analysis |
title_short | A Smart Spoofing Face Detector by Display Features Analysis |
title_sort | smart spoofing face detector by display features analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4970178/ https://www.ncbi.nlm.nih.gov/pubmed/27455259 http://dx.doi.org/10.3390/s16071136 |
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