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Fingerprint Verification System Using Combined Minutiae and Cross Correlation Based Matching

机译:结合细节和互相关的匹配指纹验证系统

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An effective system to verify human identity is a major challenge in most traditional access control systems in developing countries, as it can easily be compromised. From the vulnerability of banking transactions to the multiple registration in most civic identification projects like voters' registration, Payroll System and Pension Scheme underscores the urgent need for an effective system that provide immediate technological solution. This research work presents an Automated Fingerprint Verification System simulating both Minutiae Based Matching and Cross Correlation Coefficient Matching that provides an effective and efficient means of verifying human identity which significantly decreases the possibility of fraud in access control. The method used MATLAB simulation to align the minutiae of the two-fingerprint image (query template) and stored templates (reference template) inputted to find the total number of minutiae matched. After alignment, two minutiae are considered for matching when spatial distance and direction difference between them are not up to a given tolerance. Finally, the templates were further verified with cross correlation algorithm to improve the result accuracy. This approach has better performance as compared to individual matching technique. The result obtained after testing several fingerprints for identification proved to be efficient by verifying correctly the identities of the persons enrolled and achieving a matching score above 80% threshold for Matching Pair and below 80% threshold for Non-Matching Pair.
机译:在发展中国家大多数传统的访问控制系统中,一种有效的用于验证人类身份的系统是一个重大挑战,因为它很容易受到损害。从银行交易的脆弱性到大多数公民身份识别项目(如选民登记)中的多重注册,薪资系统和退休金计划突显了对提供即时技术解决方案的有效系统的迫切需求。这项研究工作提出了一种自动指纹验证系统,该系统可以同时模拟基于细节的匹配和互相关系数匹配,从而提供了一种有效且高效的方法来验证人的身份,从而大大降低了访问控制中欺诈的可能性。该方法使用MATLAB仿真来对齐两指纹图像的细节(查询模板)和输入的存储模板(参考模板),以找到匹配的细节总数。对齐后,当两个细节之间的空间距离和方向差未达到给定的公差时,将考虑两个细节进行匹配。最后,使用互相关算法对模板进行进一步验证,以提高结果的准确性。与单个匹配技术相比,此方法具有更好的性能。通过正确验证已注册人员的身份并达到匹配对阈值高于80%阈值和非匹配对阈值80%之下的匹配分数,证明测试了多个指纹以进行识别后获得的结果是有效的。

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