Performance Analysis of Hybrid Fingerprint Matching Methods

被引:0
|
作者
Kim, Jong Ku [1 ]
Chae, Seung-Hoon [1 ]
Lim, Sung Jin [1 ]
Pan, Sung Bum [1 ]
Moon, Daesung [2 ]
机构
[1] Chosun Univ, Dept Informat & Commun Engn, Kwangju, South Korea
[2] ETRI, Biomet Technol Res Team, Kwangju, South Korea
来源
FGCN: PROCEEDINGS OF THE 2008 SECOND INTERNATIONAL CONFERENCE ON FUTURE GENERATION COMMUNICATION AND NETWORKING, VOLS 1 AND 2 | 2008年
关键词
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Fingerprint verification in biometric technologies is the most widely-used user identification method because of its confidence and convenience. The minutiae-based method has been frequently used, but it has limitations in performance. These days, there have been many studies on enhancement of performance using other information rather than minutiae. The image-based method uses contrast of images to verify fingerprints. This study analyzed changes in performance according to size and form of images to be compared to identify the performance of the verification using binary fingerprint images. The results showed that the performance was good when the center of fingerprints was included while Zero False Match Rate(ZeroFMR) decreased when the size of compared area was below 64x64. And when the compared area was the center of the fingerprint image, verification and security performance were enhanced. In particular, if information on ridge in the center of the image was used, ZeroFAR could be evaluated though the ridge and valley were not used together.
引用
收藏
页码:562 / +
页数:2
相关论文
共 50 条
  • [31] Stacking Fingerprint Matching Algorithms for Latent Fingerprint Identification
    Valdes-Ramirez, Danilo
    Angel Medina-Perez, Miguel
    Monroy, Raul
    PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS (CIARP 2019), 2019, 11896 : 230 - 240
  • [32] Analysis of the Selection Techniques of Fingerprint Appearing Methods
    Zhang, Xiaomei
    2012 INTERNATIONAL CONFERENCE ON EDUCATION REFORM AND MANAGEMENT INNOVATION (ERMI 2012), VOL 4, 2013, : 291 - 293
  • [33] Fingerprint matching by genetic algorithms
    Tan, XJ
    Bhanu, B
    PATTERN RECOGNITION, 2006, 39 (03) : 465 - 477
  • [34] An efficient algorithm for fingerprint matching
    Wang, Chengfeng
    Gavrilova, Marina
    Luo, Yuan
    Rokne, Jon
    18TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 1, PROCEEDINGS, 2006, : 1034 - +
  • [35] Fingerprint matching using ARTMAP
    Sumathi, CP
    Santhanam, T
    Easwarakumar, KS
    Prasad, B
    INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 2004, 12 : 15 - 30
  • [36] Latent Fingerprint Matching: A Survey
    Sankaran, Anush
    Vatsa, Mayank
    Singh, Richa
    IEEE ACCESS, 2014, 2 : 982 - 1004
  • [37] Unsupervised hierarchial fingerprint matching
    Ozbayoglu, AM
    Dagli, CH
    1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, 1997, : 1439 - 1442
  • [38] Fingerprint matching with an evolutionary approach
    Sheng, W.
    Howells, G.
    Harmer, K.
    Fairhurst, M. C.
    Deravi, F.
    ADVANCES IN BIOMETRICS, PROCEEDINGS, 2007, 4642 : 484 - +
  • [39] Fingerprint matching using ANFIS
    Hong, H
    Jian-Hua, L
    2003 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-5, CONFERENCE PROCEEDINGS, 2003, : 217 - 222
  • [40] A memetic fingerprint matching algorithm
    Sheng, Weiguo
    Howells, Gareth
    Fairhurst, Michael
    Deravi, Farzin
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2007, 2 (03) : 402 - 412