Abstract
Fingerprint recognition technology as a promising high-tech has been widely applied in many fields. Fingerprint matching is one of the most important aspects. The biggest challenge is how to improve the recognition performance, when fingerprint images are with low quality and nonlinear deformation. An improved fingerprint match algorithm is proposed in this paper, which is based on key minutiae and optimal statistical registration. First, this algorithm not only combines the global matching with local matching, but also uses the optimal statistical idea to evaluate the best parameters of rotation and translation between two images. Second, this paper uses local greedy method to get the corresponding key minutia pairs. Experimental results show that the proposed algorithm can rival those advanced algorithms in the world.
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Zhang, Y., Fang, S., Zhou, B., Huang, C., Li, Y. (2014). Fingerprint Match Based on Key Minutiae and Optimal Statistical Registration. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_23
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DOI: https://doi.org/10.1007/978-3-319-12484-1_23
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12483-4
Online ISBN: 978-3-319-12484-1
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