dc.contributor.author |
Darlow, LN
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|
dc.contributor.author |
Webb, L
|
|
dc.contributor.author |
Botha, N
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|
dc.date.accessioned |
2016-11-29T09:57:58Z |
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dc.date.available |
2016-11-29T09:57:58Z |
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dc.date.issued |
2016-05 |
|
dc.identifier.citation |
Darlow, L.N., Webb, L. and Botha, N. 2016. Automated spoof-detection for fingerprints using optical coherence tomography. Applied Optics, 55(13), 3387-3396 |
en_US |
dc.identifier.issn |
1559-128X |
|
dc.identifier.uri |
https://www.osapublishing.org/ao/abstract.cfm?uri=ao-55-13-3387
|
|
dc.identifier.uri |
http://hdl.handle.net/10204/8863
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|
dc.description |
Copyright: 2015 OSA Publishing. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in Applied Optics, 55(13), 3387-3396 |
en_US |
dc.description.abstract |
Fingerprint recognition systems are prevalent in high-security applications. As a result, the act of spoofing these systems with artificial fingerprints is of increasing concern. This research presents an automatic means for spoof-detection using optical coherence tomography (OCT). This technology is able to capture a 3D representation of the internal structure of the skin and is thus not limited to a 2D surface scan. The additional information afforded by this representation means that accurate spoof-detection can be achieved. Two features were extracted to detect the presence of (1) an additional thin layer on the surface of the skin and (2) a thicker additional layer or a complete artificial finger. An analysis of these features showed that they are highly separable, resulting in 100% accuracy regarding spoof-detection, with no false rejections of real fingers. This is the first attempt at fully automated spoof-detection using OCT. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
OSA Publishing |
en_US |
dc.relation.ispartofseries |
Workflow;17097 |
|
dc.subject |
Optical coherence tomography |
en_US |
dc.subject |
OCT |
en_US |
dc.subject |
Image processing |
en_US |
dc.subject |
Tomographic image processing |
en_US |
dc.subject |
Fingerprint recognition systems |
en_US |
dc.subject |
High-security applications |
en_US |
dc.title |
Automated spoof-detection for fingerprints using optical coherence tomography |
en_US |
dc.type |
Article |
en_US |
dc.identifier.apacitation |
Darlow, L., Webb, L., & Botha, N. (2016). Automated spoof-detection for fingerprints using optical coherence tomography. http://hdl.handle.net/10204/8863 |
en_ZA |
dc.identifier.chicagocitation |
Darlow, LN, L Webb, and N Botha "Automated spoof-detection for fingerprints using optical coherence tomography." (2016) http://hdl.handle.net/10204/8863 |
en_ZA |
dc.identifier.vancouvercitation |
Darlow L, Webb L, Botha N. Automated spoof-detection for fingerprints using optical coherence tomography. 2016; http://hdl.handle.net/10204/8863. |
en_ZA |
dc.identifier.ris |
TY - Article
AU - Darlow, LN
AU - Webb, L
AU - Botha, N
AB - Fingerprint recognition systems are prevalent in high-security applications. As a result, the act of spoofing these systems with artificial fingerprints is of increasing concern. This research presents an automatic means for spoof-detection using optical coherence tomography (OCT). This technology is able to capture a 3D representation of the internal structure of the skin and is thus not limited to a 2D surface scan. The additional information afforded by this representation means that accurate spoof-detection can be achieved. Two features were extracted to detect the presence of (1) an additional thin layer on the surface of the skin and (2) a thicker additional layer or a complete artificial finger. An analysis of these features showed that they are highly separable, resulting in 100% accuracy regarding spoof-detection, with no false rejections of real fingers. This is the first attempt at fully automated spoof-detection using OCT.
DA - 2016-05
DB - ResearchSpace
DP - CSIR
KW - Optical coherence tomography
KW - OCT
KW - Image processing
KW - Tomographic image processing
KW - Fingerprint recognition systems
KW - High-security applications
LK - https://researchspace.csir.co.za
PY - 2016
SM - 1559-128X
T1 - Automated spoof-detection for fingerprints using optical coherence tomography
TI - Automated spoof-detection for fingerprints using optical coherence tomography
UR - http://hdl.handle.net/10204/8863
ER -
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en_ZA |