NDLI: Fast pore matching method based on deterministic annealing algorithm

Content Provider	IET Digital Library
Author	Lu, Guangming Xu, Yuanrong
Abstract	High-resolution fingerprint identification system (HRFIS) has become a hot topic in the field of academic research. Compared to traditional automatic fingerprint identification system, HRFIS reduces the risk of being faked by using level 3 features, such as pores, which cannot be detected in lower resolution images. However, there is a serious problem in HRFIS: there are hundreds of sweat pores in one fingerprint image, which will spend a considerable amount of time for direct fingerprint matching. The authors propose a method to match pores in two fingerprint images based on deterministic annealing algorithm. In this method, fingerprints are aligned using singular points. Then minutiae are matched based on the alignment result. To reduce the impact of deformation, they build a convex hull for each of these fingerprints. Pores in these convex hulls are used for matching. In the experiments, their method is compared with random sample consensus method, minutia and ICP-based method, and direct pore matching method. The results show that the proposed method is more efficient.
Starting Page	1034
Ending Page	1040
Page Count	7
ISSN	17519659
Volume Number	11
e-ISSN	17519667
Issue Number	Issue 11, Nov (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/11/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0138
Journal	IET Image Processing
Publisher Date	2017-07-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Combinatorial Mathematics Computer Vision And Image Processing Technique Convex Hulls Deterministic Annealing Algorithm Fast Pore Matching Method Fingerprint Identification High-resolution Fingerprint Identification System HRFIS Image Matching Image Recognition Optimisation Technique Set Theory Simulated Annealing Singular Point
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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