【摘要】 两幅指纹之间的“配准模式”是由所有局部最优配准决定的.由假匹配产生的配准模式与真匹配的配准模式是不同的,尽管假匹配的两幅指纹图像从细节点的角度来看有很高的相似度.提出一种用细节点、联系脊线和方向场特征信息确定配准模式并进行指纹匹配的算法.算法由两部分组成:离线学习部分从一组真匹配数据中获得一个真配准模式集;在线部分对待匹配的指纹作配准并确定其配准模式,仅当该模式构成一个真模式时,才做进一步的精细匹配.真配准模式集是由对NIST24连续指纹影像数据集的计算获取的.在FVC2002DB2数据库上的测试显示,算法有很高的准确率.更多还原

【Abstract】 The “registration pattern” between two fingerprints is the optimal registration of each part of one fingerprint with respect to the other fingerprint. Registration patterns generated from imposter’s matching attempts are different from those patterns from genuine matching attempts, although they may share some similarities in the aspect of minutiae. This paper presents an algorithm that utilizes minutiae, associate ridges and orientation fields to determine the registration pattern between two fingerprints and their similarity. The proposed matching scheme has two stages. An offline training stage derives a genuine registration pattern base from a set of genuine matching attempts. Then, an online matching stage registers the two fingerprints and determines the registration pattern. Only if the pattern makes a genuine one, a further fine matching is conducted. The genuine registration pattern base is derived using a set of fingerprints extracted from the NIST Special Database 24. Experimental results on the second FVC2002 database demonstrate the performance of the proposed algorithm.更多还原