Fingerprint matching using OrientationCodes and PolyLines
Pattern Recognition
Fingerprint verification using mutual information
Journal of Computing Sciences in Colleges
Differential Evolution as a viable tool for satellite image registration
Applied Soft Computing
Consensus fingerprint matching with genetically optimised approach
Pattern Recognition
High resolution partial fingerprint alignment using pore-valley descriptors
Pattern Recognition
Sweeping fingerprint verification system based on template matching
ICNVS'10 Proceedings of the 12th international conference on Networking, VLSI and signal processing
A sweeping fingerprint verification system using the template matching method
WSEAS Transactions on Computers
Journal of Biomedical Imaging
Feature based image registration using non-degenerate pixels
Signal Processing
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Fingerprint registration is a critical step in fingerprint matching. Although a variety of registration alignment algorithms have been proposed, accurate fingerprint registration remains an unresolved problem. We propose a new algorithm for fingerprint registration using orientation field. This algorithm finds the correct alignment by maximization of mutual information between features extracted from orientation fields of template and input fingerprint images. Orientation field, representing the flow of ridges, is a relatively stable global feature of fingerprint images. This method uses the statistics and distribution of global feature of fingerprint images so that it is robust to image quality and local changes in images. The primary characteristic of this method is that it uses this stable global feature to align fingerprints, and that its behavior may resemble the way humans compare fingerprints. Experimental results show that the occurrence of misalignment is dramatically reduced and that registration accuracy is greatly improved at the same time, leading to enhanced matching performance.