On-Line Fingerprint Verification
Anil Jain, Fellow, IEEE, Lin Hong, and Ruud Bolle, Fellow, IEEE
Abstract—Fingerprint verification is one of the most reliable personal identification methods. However, manual fingerprint verification is so tedious, time-consuming, and expensive that it is incapable of meeting today’s increasing performance requirements. An automatic fingerprint identification system (AFIS) is widely needed. It plays a very important role in forensic and civilian applications such as criminal identification, access control, and ATM card verification. This paper describes the design and implementation of an on-line 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., which is much faster and more reliable, is implemented for extracting features from an input fingerprint image captured with an on-line 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 on-line verification with high accuracy.
Index Terms—Biometrics, fingerprints, matching, verification, minutia, orientation field, ridge extraction.
实时指纹验证
IEEE会员 林宏, 万一飞, IEEE会员 Anil Jain
摘要：指纹验证可以说是一种最可靠的个人身份验证的方法。但是手动的指纹验证方法由于其单调乏味，费时，加上费用昂贵，已经不能满足当今日益增多的实际运用的需要。相应的，人们越来越需要一种自动的指纹验证系统（AFIS）。它在司法和民用上都起到了非常重要的作用。例如罪犯的辨认，计算机的访问控制和在ATM自动取款功能中人的身份验证。本文介绍了一种快速指纹自动识别系统在操作运行时的两个阶段：指纹细节的提取和细节的匹配。Ratha.et.al提出了一种改良过的提取指纹细节的算法，其运算速度更快，可信度更高。他通过一部高速无墨的扫描仪来实现指纹部分细节特征的提取。在细节匹配这个问题上，已经建立了基于弹性匹配的算法。这种算法能够不通过其他的辅助手段找出提取出的指纹与已存指纹模板之间的联系。并且它能修正和补偿由于指纹的非线性变形和位置不精确所造成的误差。这种算法已经在两套无墨指纹采集装置上测试过，并且获得了令人满意的精确度。一般的，一个完善的指纹识别系统在有20个工作站的SPARC系统上的平均响应时间为8秒。实验结果表明，我们的系统在实时指纹验证上能满足响应时间的要求，有很高的精确度。
