一种基于细节点全局置信度的指纹匹配算法

An Fingerprint Matching Algorithm Based on Minutia Global Confidence

传统基于细节点的指纹匹配方法通常利用细节点的局部结构相似度来描述一组细节点对之间的匹配程度.提出细节点的全局置信度概念,描述一组细节点对在全局范围内与其他细节点对之间的空间一致性和整体匹配可能性,可看作是对局部相似度的一个有效补充.通过计算点对相容性矩阵的主特征向量,借助谱松弛技术,可得到所有细节点对的全局置信度.结合局部相似度和全局置信度可构造出新的关联矩阵,那些具有较大的局部相似度和较大的全局置信度的候选细节点对被认定是匹配的.该方法较好地利用局部拓扑信息和全局相容信息,对非刚性形变和噪声具有较好的鲁棒性.在FVC2002和FVC2004数据库上的实验结果表明,该方法具有较高的效率和准确性.

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.