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On-line fingerprint verification

机译:在线指纹验证

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摘要

Fingerprint verification is one of the most reliable personal identification methods. However, manual fingerprint verification is incapable of meeting today's increasing performance requirements. An automatic fingerprint identification system (AFIS) is needed. This paper describes the design and implementation of an online fingerprint verification system which operates in two stages: minutia extraction and minutia matching. An improved version of the minutia extraction algorithm proposed by Ratha et al. (1995), which is much faster and more reliable, is implemented for extracting features from an input fingerprint image captured with an online inkless scanner. For minutia matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the correspondences between minutiae in the input image and the stored template without resorting to exhaustive search and has the ability of adaptively compensating for the nonlinear deformations and inexact pose transformations between fingerprints. The system has been tested on two sets of fingerprint images captured with inkless scanners. The verification accuracy is found to be acceptable. Typically, a complete fingerprint verification procedure takes, on an average, about eight seconds on a SPARC 20 workstation. These experimental results show that our system meets the response time requirements of online verification with high accuracy.
机译:指纹验证是最可靠的个人识别方法之一。但是,手动指纹验证无法满足当今不断增长的性能要求。需要一个自动指纹识别系统(AFIS)。本文介绍了在线指纹验证系统的设计和实现,该系统分两个阶段运行:细节提取和细节匹配。 Ratha等人提出的Minutia提取算法的改进版本。 (1995年),它是更快和更可靠的实现,用于从使用在线无墨扫描仪捕获的输入指纹图像中提取特征。对于细节匹配,已经开发了基于对齐的弹性匹配算法。该算法能够在不借助穷举搜索的情况下找到输入图像中细节与所存储模板之间的对应关系,并且能够自适应地补偿指纹之间的非线性变形和不精确的姿态变换。该系统已经在使用无墨扫描仪捕获的两组指纹图像上进行了测试。发现验证准确性是可以接受的。通常,在SPARC 20工作站上,完整的指纹验证过程平均大约需要八秒钟。这些实验结果表明,我们的系统可以高精度地满足在线验证的响应时间要求。

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