Fingerprint Singular Points Detection and Direction Estimation with a “T” Shape Model

As a sort of evident landmark features of fingerprints, singular points (SPs) play important roles in fingerprint alignment, classification and recognition. We present an adaptive “T” shape model of SPs and develop a robust and generic approach to detect SPs and their directions simultaneously. The...

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Bibliographic Details
Published inAudio- and Video-Based Biometric Person Authentication pp. 201 - 207
Main Authors Liu, Tong, Hao, Pengwei, Zhang, Chao
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Direction Estimation
Exact sciences and technology
Fingerprint Image
Fingerprint Pattern
Pattern recognition. Digital image processing. Computational geometry
Shape Model
Singular Point
Biometrics
Alignment
Fingerprint
Model-based reasoning
Image processing
Fingerprint identification
Point estimation
Classification
Singular point
Database
Modeling
Adaptive method
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Summary:As a sort of evident landmark features of fingerprints, singular points (SPs) play important roles in fingerprint alignment, classification and recognition. We present an adaptive “T” shape model of SPs and develop a robust and generic approach to detect SPs and their directions simultaneously. The proposed approach utilizes homocentric sectors around candidate SPs to pick out lateral-axes and further main-axes based on the proposed model. The results of the experiment conducted on a public database, FVC 2002, demonstrate the effectiveness of the method in this paper.
ISBN:9783540278870
3540278877
ISSN:0302-9743
1611-3349
DOI:10.1007/11527923_21