Minutiae set to bit-string conversion using multi-scale bag-of-words paradigm

Wei Jing Wong; M. L. Dennis Wong; Yau Hee Kho; Andrew Beng; Jin Teoh

doi:10.1109/WIFS.2014.7084294

Minutiae set to bit-string conversion using multi-scale bag-of-words paradigm

Wei Jing Wong, M. L. Dennis Wong, Yau Hee Kho, Andrew Beng, Jin Teoh

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

3 Citations (Scopus)

Abstract

Minutiae-based matching is commonly used in fingerprint recognition systems due to its proven performance. However, such matching procedure usually involves unordered and variable size templates and it does not favour emerging bio-cryptography applications and most classifiers. This paper proposes a solution by converting the original minutiae set into a bit-string through the amalgamation of bag-of-words modelling, multi-scale construction and dynamic quantization. Experimental results show that the proposed method has high potential in biocryptography applications due to its outstanding EER of < 0:51% and entropy of 723 bits. Further security and privacy concerns are also analyzed.

Original language	English
Title of host publication	2014 IEEE International Workshop on Information Forensics and Security, WIFS 2014
Publisher	IEEE
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781479988822
DOIs	https://doi.org/10.1109/WIFS.2014.7084294
Publication status	Published - Apr 2015
Event	2014 IEEE International Workshop on Information Forensics and Security, WIFS 2014 - Atlanta, United States Duration: 3 Dec 2014 → 5 Dec 2014

Conference

Conference	2014 IEEE International Workshop on Information Forensics and Security, WIFS 2014
Country	United States
City	Atlanta
Period	3/12/14 → 5/12/14

Keywords

Fingerprint recognition
minutiae-based matching
multi-line code
multi-scale bag-of-words

ASJC Scopus subject areas

Computer Science Applications
Information Systems
Information Systems and Management
Safety, Risk, Reliability and Quality

Access to Document

10.1109/WIFS.2014.7084294

Link to publication in Scopus

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Cite this

Wong, W. J., Wong, M. L. D., Kho, Y. H., Beng, A., & Teoh, J. (2015). Minutiae set to bit-string conversion using multi-scale bag-of-words paradigm. In 2014 IEEE International Workshop on Information Forensics and Security, WIFS 2014 (pp. 1-6). [7084294] IEEE. https://doi.org/10.1109/WIFS.2014.7084294

@inproceedings{8a9b2f5f500240b08c99dca74f57fdd0,

title = "Minutiae set to bit-string conversion using multi-scale bag-of-words paradigm",

abstract = "Minutiae-based matching is commonly used in fingerprint recognition systems due to its proven performance. However, such matching procedure usually involves unordered and variable size templates and it does not favour emerging bio-cryptography applications and most classifiers. This paper proposes a solution by converting the original minutiae set into a bit-string through the amalgamation of bag-of-words modelling, multi-scale construction and dynamic quantization. Experimental results show that the proposed method has high potential in biocryptography applications due to its outstanding EER of < 0:51% and entropy of 723 bits. Further security and privacy concerns are also analyzed.",

keywords = "Fingerprint recognition, minutiae-based matching, multi-line code, multi-scale bag-of-words",

author = "Wong, {Wei Jing} and Wong, {M. L. Dennis} and Kho, {Yau Hee} and Andrew Beng and Jin Teoh",

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Wong, WJ, Wong, MLD, Kho, YH, Beng, A & Teoh, J 2015, Minutiae set to bit-string conversion using multi-scale bag-of-words paradigm. in 2014 IEEE International Workshop on Information Forensics and Security, WIFS 2014., 7084294, IEEE, pp. 1-6, 2014 IEEE International Workshop on Information Forensics and Security, WIFS 2014, Atlanta, United States, 3/12/14. https://doi.org/10.1109/WIFS.2014.7084294

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AB - Minutiae-based matching is commonly used in fingerprint recognition systems due to its proven performance. However, such matching procedure usually involves unordered and variable size templates and it does not favour emerging bio-cryptography applications and most classifiers. This paper proposes a solution by converting the original minutiae set into a bit-string through the amalgamation of bag-of-words modelling, multi-scale construction and dynamic quantization. Experimental results show that the proposed method has high potential in biocryptography applications due to its outstanding EER of < 0:51% and entropy of 723 bits. Further security and privacy concerns are also analyzed.

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