Machine Vision and Applications
Combining fingerprint matchers based on D-S evidence theory
SPPRA'06 Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications
Coarse fingerprint registration using orientation fields
EURASIP Journal on Applied Signal Processing
Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles
IEICE - Transactions on Information and Systems
Recovery of 3D Solar Magnetic Field Model Parameter Using Image Structure Matching
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
High resolution partial fingerprint alignment using pore-valley descriptors
Pattern Recognition
Brief paper: Fingerprint matching using multi-dimensional ANN
Engineering Applications of Artificial Intelligence
Using genetic algorithms for fingerprint core point detection
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
Biometric mobile template protection: a composite feature based fingerprint fuzzy vault
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Fingerprint singular points detection and direction estimation with a “t” shape model
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
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Fingerprint matching algorithm is a key issue of the fingerprint recognition, and there already exist many fingerprint matching algorithms, According to the dependence of the core point, fingerprint matching algorithms are divided into two groups, core-based match algorithms and noncore-based match algorithms. Most of the noncore-based matching algorithm is time consuming, therefore, they are not suitable for online application; meanwhile, the core-based matching algorithm is efficient than the noncore-based matching algorithm, but it highly depends on the core detection precision. In this paper, we present a new core-based structure matching algorithm which considers both efficient and precision. Firstly we used core detection algorithm to get the core position, then we define some local structure of the core area. Used these local structure, we can find some correspondent points of the two fingerprint image. Secondly, we use the correspondent points in the first stage to match the global feature of the fingerprint. Experimental results show that the performance of the proposed algorithm is good.