research-article

A Region-based Alignment-free Partial Fingerprint Matching

Authors:

David Albrecht,

Nandita Bhattacharjee,

Bala SrinivasanAuthors Info & Claims

MoMM '16: Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media

Pages 63 - 70

https://doi.org/10.1145/3007120.3007130

Published: 28 November 2016 Publication History

Abstract

Fingerprint is one of the most researched biometrics and applied to many applications like boarder security, access security, security of electronic devices to name a few. However, alignment and matching of partial fingerprints convincingly is still a challenging problem. This paper proposes a region based partial fingerprint matching approach that matches the fingerprints without aligning them. The approach focuses on extracting the matching regions in unaligned fingerprints. As extraction of regions happens without alignment, a new similarity metric is proposed that can compute similarity value between unaligned fingerprints. The results demonstrate that the proposed approach can eliminate the need for aligning the fingerprints without affecting the accuracy. The popular Fingerprint Verification Competition (FVC) 2002 dataset is used for conducting experiments. Moreover, the results of fingerprint recognition are compared with the best alignment based fingerprint matching techniques.

References

[1]

R. Cappelli, D. Maio, D. Maltoni, J. L. Wayman, and A. K. Jain. Performance evaluation of fingerprint verification systems. IEEE transactions on pattern analysis and machine intelligence, 28(1):3--18, 2006.

Digital Library

[2]

S. R. Deans. The Radon transform and some of its applications. Courier Corporation, 2007.

[3]

M. Ferrara, D. Maltoni, and R. Cappelli. Noninvertible minutia cylinder-code representation. IEEE Transactions on Information Forensics and Security, 7(6):1727--1737, 2012.

Digital Library

[4]

Z. Gao, X. You, L. Zhou, and W. Zeng. A novel matching technique for fingerprint recognition by graphical structures. In Wavelet Analysis and Pattern Recognition (ICWAPR), 2011 International Conference on, pages 77--82. IEEE, 2011.

[5]

F. Hjouj and D. W. Kammler. Identification of reflected, scaled, translated, and rotated objects from their radon projections. IEEE Transactions on Image Processing, 17(3):301--310, 2008.

Digital Library

[6]

T.-Y. Jea, V. S. Chavan, V. Govindaraju, and J. K. Schneider. Security and matching of partial fingerprint recognition systems. In Defense and Security, pages 39--50. International Society for Optics and Photonics, 2004.

[7]

D. K. Karna, S. Agarwal, and S. Nikam. Normalized cross-correlation based fingerprint matching. In Computer Graphics, Imaging and Visualisation, 2008. CGIV'08. Fifth International Conference on, pages 229--232. IEEE, 2008.

Digital Library

[8]

R. D. Labati and F. Scotti. Fingerprint. In Encyclopedia of Cryptography and Security, pages 460--465. Springer, 2011.

[9]

D. Maio, D. Maltoni, R. Cappelli, J. L. Wayman, and A. K. Jain. Fvc2002: Second fingerprint verification competition. In Pattern recognition, 2002. Proceedings. 16th international conference on, volume 3, pages 811--814. IEEE, 2002.

Digital Library

[10]

D. Maltoni, D. Maio, A. Jain, and S. Prabhakar. Handbook of fingerprint recognition. Springer Science & Business Media, 2009.

Digital Library

[11]

R. Mooser, F. Forsberg, E. Hack, G. Székely, and U. Sennhauser. Estimation of affine transformations directly from tomographic projections in two and three dimensions. Machine vision and applications, 24(2):419--434, 2013.

[12]

N. Nacereddine, S. Tabbone, and D. Ziou. Object recognition using radon transform-based rst parameter estimation. In International Conference on Advanced Concepts for Intelligent Vision Systems, pages 515--526. Springer, 2012.

Digital Library

[13]

N. Nacereddine, S. Tabbone, and D. Ziou. Similarity transformation parameters recovery based on radon transform. application in image registration and object recognition. Pattern Recognition, 48(7):2227--2240, 2015.

Digital Library

[14]

K. Nandakumar and A. K. Jain. Local correlation-based fingerprint matching. In ICVGIP, pages 503--508, 2004.

[15]

S. Pankanti, S. Prabhakar, and A. K. Jain. On the individuality of fingerprints. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24(8):1010--1025, 2002.

Digital Library

[16]

A. P. Papliński. The angular integral of the radon transform (anirt) as a feature vector in categorization of visual objects. In Advances in Neural Networks--ISNN 2013, pages 523--531. Springer, 2013.

Digital Library

[17]

A. G. Ramm and A. I. Katsevich. The Radon transform and local tomography. CRC press, 1996.

[18]

D. Singpurwalla. A handbook of statistics: An overview of statistical methods. 2013.

[19]

M. Tico and P. Kuosmanen. Fingerprint matching using an orientation-based minutia descriptor. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 25(8):1009--1014, 2003.

Digital Library

[20]

B. T. Ulery, R. A. Hicklin, J. Buscaglia, and M. A. Roberts. Accuracy and reliability of forensic latent fingerprint decisions. Proceedings of the National Academy of Sciences, 108(19):7733--7738, 2011.

[21]

J. C. Yang, J. W. Shin, and D. S. Park. Fingerprint matching using invariant moment features. In International Conference on Computational and Information Science, pages 1029--1038. Springer, 2006.

[22]

O. Zanganeh, B. Srinivasan, and N. Bhattacharjee. Partial fingerprint matching through region-based similarity. In Digital lmage Computing: Techniques and Applications (DlCTA), 2014 International Conference on, pages 1--8. IEEE, 2014.

[23]

Y. Zhang, X. Yang, Q. Su, and J. Tian. Fingerprint recognition based on combined features. In Advances in Biometrics, pages 281--289. Springer, 2007.

Digital Library

[24]

J. Zhou, F. Chen, and J. Gu. A novel algorithm for detecting singular points from fingerprint images. IEEE transactions on pattern analysis and machine intelligence, 31(7):1239--1250, 2009.

Digital Library

Cited By

SHABRINA NLI DISSHIKI T(2024)High Precision Fingerprint Verification for Small Area Sensor Based on Deep LearningIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences10.1587/transfun.2022EAP1079E107.A:1(157-168)Online publication date: 1-Jan-2024
https://doi.org/10.1587/transfun.2022EAP1079
Komal KBhattacharjee NAlbrecht DSrinivasan B(2018)Parameter Recovery Using Radon TransformProceedings of the 16th International Conference on Advances in Mobile Computing and Multimedia10.1145/3282353.3282361(34-43)Online publication date: 19-Nov-2018
https://dl.acm.org/doi/10.1145/3282353.3282361
Sabir M(2018)Sensitivity and Specificity Analysis of Fingerprints Based Algorithm2018 International Conference on Applied and Engineering Mathematics (ICAEM)10.1109/ICAEM.2018.8536268(1-5)Online publication date: Sep-2018
https://doi.org/10.1109/ICAEM.2018.8536268
Show More Cited By

Recommendations

Design of Alignment-Free Cancelable Fingerprint Templates with Zoned Minutia Pairs

Cancelable fingerprint templates effectively protect original fingerprint data by revoking a compromised template and reissuing a new one. Alignment-free cancelable templates require no image pre-alignment and therefore do not suffer from inaccurate ...
A robust fingerprint matching method

This paper is concerned with accurate and efficient fingerprint matching. We have two main contributions:(1)define a novel feature vector for each fingerprint minutia based on the global orientation field. These features are used to identify ...
An alignment-free fingerprint cryptosystem based on fuzzy vault scheme

Fuzzy vault is a practical and promising scheme, which can protect biometric templates and perform secure key management simultaneously. Alignment of the template biometric sample and the query one in the encrypted domain remains a challenging task. ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

MoMM '16: Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media

November 2016

363 pages

ISBN:9781450348065

DOI:10.1145/3007120

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

@WAS: International Organization of Information Integration and Web-based Applications and Services

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 November 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

MoMM '16

MoMM '16: 14th International Conference on Advances in Mobile Computing and Multi Media

November 28 - 30, 2016

Singapore, Singapore

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
89
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)1

Reflects downloads up to 15 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

SHABRINA NLI DISSHIKI T(2024)High Precision Fingerprint Verification for Small Area Sensor Based on Deep LearningIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences10.1587/transfun.2022EAP1079E107.A:1(157-168)Online publication date: 1-Jan-2024
https://doi.org/10.1587/transfun.2022EAP1079
Komal KBhattacharjee NAlbrecht DSrinivasan B(2018)Parameter Recovery Using Radon TransformProceedings of the 16th International Conference on Advances in Mobile Computing and Multimedia10.1145/3282353.3282361(34-43)Online publication date: 19-Nov-2018
https://dl.acm.org/doi/10.1145/3282353.3282361
Sabir M(2018)Sensitivity and Specificity Analysis of Fingerprints Based Algorithm2018 International Conference on Applied and Engineering Mathematics (ICAEM)10.1109/ICAEM.2018.8536268(1-5)Online publication date: Sep-2018
https://doi.org/10.1109/ICAEM.2018.8536268
Schuch P(2018)Survey on features for fingerprint indexingIET Biometrics10.1049/iet-bmt.2017.02798:1(1-13)Online publication date: 28-Sep-2018
https://doi.org/10.1049/iet-bmt.2017.0279
Komal KBhattacharjee NAlbrecht DSrinivasan B(2017)Transformational Approach for Alignment-free Image Matching ApplicationsProceedings of the 15th International Conference on Advances in Mobile Computing & Multimedia10.1145/3151848.3151855(49-57)Online publication date: 4-Dec-2017
https://dl.acm.org/doi/10.1145/3151848.3151855
Shah BPanchal G(2017)Comparative analysis on different Region of Interest (RoI) extraction mechanisms for fingerprint2017 International Conference on Intelligent Sustainable Systems (ICISS)10.1109/ISS1.2017.8389261(690-694)Online publication date: Dec-2017
https://doi.org/10.1109/ISS1.2017.8389261

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents