Fingerprint liveness detection based on multiple image quality features

Changlong Jin; Shengzhe Li; Hakil Kim; Ensoo Park

doi:10.1007/978-3-642-17955-6_21

Fingerprint liveness detection based on multiple image quality features

Changlong Jin, Shengzhe Li, Hakil Kim, Ensoo Park

Inha University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

Recent studies have shown that the conventional fingerprint recognition systems are vulnerable to fake attacks, and there are many existing systems that need to update their anti-spoofing capability inexpensively. This paper proposes an image quality-based fake detection method to address this problem. Three effective fake/live quality measures, spectral band energy, middle ridge line and middle valley line, are extracted firstly, and then, these features are fused and tested on a fake/live dataset using SVM and QDA classifiers. Experimental results demonstrate that the proposed method is promising in increasing the security of the existing fingerprint authentication system by only updating the software.

Original language	English
Title of host publication	Information Security Applications - 11th International Workshop, WISA 2010, Revised Selected Papers
Publisher	Springer Verlag
Pages	281-291
Number of pages	11
ISBN (Print)	3642179541, 9783642179549
DOIs	https://doi.org/10.1007/978-3-642-17955-6_21
State	Published - 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6513 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) through the Biometrics Engineering Research Center (BERC) at Yonsei University. (No.R112002105080010(2010)).

Keywords

Liveness detection
middle ridge line
middle valley line
spectral band energy

Access to Document

10.1007/978-3-642-17955-6_21

Cite this

Jin, C., Li, S., Kim, H., & Park, E. (2011). Fingerprint liveness detection based on multiple image quality features. In Information Security Applications - 11th International Workshop, WISA 2010, Revised Selected Papers (pp. 281-291). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6513 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-642-17955-6_21

Jin, Changlong ; Li, Shengzhe ; Kim, Hakil et al. / Fingerprint liveness detection based on multiple image quality features. Information Security Applications - 11th International Workshop, WISA 2010, Revised Selected Papers. Springer Verlag, 2011. pp. 281-291 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{c961d132f63148928db7e119991911b9,

title = "Fingerprint liveness detection based on multiple image quality features",

abstract = "Recent studies have shown that the conventional fingerprint recognition systems are vulnerable to fake attacks, and there are many existing systems that need to update their anti-spoofing capability inexpensively. This paper proposes an image quality-based fake detection method to address this problem. Three effective fake/live quality measures, spectral band energy, middle ridge line and middle valley line, are extracted firstly, and then, these features are fused and tested on a fake/live dataset using SVM and QDA classifiers. Experimental results demonstrate that the proposed method is promising in increasing the security of the existing fingerprint authentication system by only updating the software.",

keywords = "Liveness detection, middle ridge line, middle valley line, spectral band energy",

author = "Changlong Jin and Shengzhe Li and Hakil Kim and Ensoo Park",

note = "Funding Information: This work was supported by the National Research Foundation of Korea (NRF) through the Biometrics Engineering Research Center (BERC) at Yonsei University. (No.R112002105080010(2010)).",

year = "2011",

doi = "10.1007/978-3-642-17955-6_21",

language = "English",

isbn = "3642179541",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "281--291",

booktitle = "Information Security Applications - 11th International Workshop, WISA 2010, Revised Selected Papers",

address = "Germany",

}

Jin, C, Li, S, Kim, H & Park, E 2011, Fingerprint liveness detection based on multiple image quality features. in Information Security Applications - 11th International Workshop, WISA 2010, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6513 LNCS, Springer Verlag, pp. 281-291. https://doi.org/10.1007/978-3-642-17955-6_21

Fingerprint liveness detection based on multiple image quality features. / Jin, Changlong; Li, Shengzhe; Kim, Hakil et al.
Information Security Applications - 11th International Workshop, WISA 2010, Revised Selected Papers. Springer Verlag, 2011. p. 281-291 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6513 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fingerprint liveness detection based on multiple image quality features

AU - Jin, Changlong

AU - Li, Shengzhe

AU - Kim, Hakil

AU - Park, Ensoo

N1 - Funding Information: This work was supported by the National Research Foundation of Korea (NRF) through the Biometrics Engineering Research Center (BERC) at Yonsei University. (No.R112002105080010(2010)).

PY - 2011

Y1 - 2011

N2 - Recent studies have shown that the conventional fingerprint recognition systems are vulnerable to fake attacks, and there are many existing systems that need to update their anti-spoofing capability inexpensively. This paper proposes an image quality-based fake detection method to address this problem. Three effective fake/live quality measures, spectral band energy, middle ridge line and middle valley line, are extracted firstly, and then, these features are fused and tested on a fake/live dataset using SVM and QDA classifiers. Experimental results demonstrate that the proposed method is promising in increasing the security of the existing fingerprint authentication system by only updating the software.

AB - Recent studies have shown that the conventional fingerprint recognition systems are vulnerable to fake attacks, and there are many existing systems that need to update their anti-spoofing capability inexpensively. This paper proposes an image quality-based fake detection method to address this problem. Three effective fake/live quality measures, spectral band energy, middle ridge line and middle valley line, are extracted firstly, and then, these features are fused and tested on a fake/live dataset using SVM and QDA classifiers. Experimental results demonstrate that the proposed method is promising in increasing the security of the existing fingerprint authentication system by only updating the software.

KW - Liveness detection

KW - middle ridge line

KW - middle valley line

KW - spectral band energy

UR - http://www.scopus.com/inward/record.url?scp=85036667257&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-17955-6_21

DO - 10.1007/978-3-642-17955-6_21

M3 - Conference contribution

AN - SCOPUS:85036667257

SN - 3642179541

SN - 9783642179549

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 281

EP - 291

BT - Information Security Applications - 11th International Workshop, WISA 2010, Revised Selected Papers

PB - Springer Verlag

ER -

Jin C, Li S, Kim H, Park E. Fingerprint liveness detection based on multiple image quality features. In Information Security Applications - 11th International Workshop, WISA 2010, Revised Selected Papers. Springer Verlag. 2011. p. 281-291. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-17955-6_21

Fingerprint liveness detection based on multiple image quality features

Abstract

Publication series

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this