Abstract：The local structural similarity is used in traditional minutia-based fingerprint matching methods to describe the potential associations of each minutia pair.The concept of minutia global confidence is proposed to define the geometric consistency and global matching possibility between one minutia pair and all the other candidate pairs. It can be seen as a supplement to local structural similarity. The global confidence of each minutia pair is acquired by calculating the principal eigenvector of the pairwise compatibility matrix and using spectral relaxation techniques. The correlation matrix can be constructed by using large local structural similarity and large global confidence. Minutia pairs with large local structural similarity and large global confidence are judged to be matched. The proposed approach utilizes the information of local topology and global compatibitity well and has better robustness. The experiments on FVC 2002 and 2004 databases demonstrate its effectiveness and efficiency.
付翔，封举富. 一种基于细节点全局置信度的指纹匹配算法*[J]. 模式识别与人工智能, 2014, 27(9): 835-840.
FU Xiang, FENG Ju-Fu. An Fingerprint Matching Algorithm Based on Minutia Global Confidence. , 2014, 27(9): 835-840.
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2014, Vol. 27 
