基于奇异点邻近结构的快速指纹识别

将指纹识别中分类和匹配过程相结合,提出了一种包含奇异点周边的方向场和细节点等特征的奇异点邻近结构.该结构利用奇异点周边识别信息集中的特点,大大减少了匹配的计算量,并能够同时作为指纹分类和比对的特征,直接应用于指纹的连续分类和快速匹配过程,实现对大容量指纹数据库的快速识别.在NIST和FVC2004数据库上的测试结果显示,该算法在保证自动指纹识别系统(automatic fingerprint identification system,简称AFIS)的识别准确性的同时,还使得指纹在线识别系统的1:N辨识速度有显著的提高.

Fast Fingerprint Identification Based on Neighborhood Structure Around Singular Point

Combining the classification and matching of fingerprints together, a neighborhood structure is proposed in this paper, which includes the orientation field and minutia around the reference singular point. This structure has the advantage that the identification information is centralized around the singular point, and can dramatically decrease the calculation of matching. It can also be directly used as pattern in both the continuous classification and the fast matching of fingerprints, and carry out the fast identification of the large scale database. Experimental results on NIST and FVC2004 databases show that this algorithm can highly speed up the matching of large scale fingerprint database with a preferable performance, and it can be used in one-to-many matching of on-line fingerprint identification system.