资 源 简 介
基于过滤器算法使用一个银行伽柏过滤器捕捉 本地和全球在指纹细节紧凑的固定长度 FingerCode。 指纹匹配是基于欧氏 两个相应的FingerCodes因此之间的距离 非常快。能够达到一个验证精度 只是略次于minutiae-based最好的结果 算法在公开文献发表。 我们的系统执行 比最先进的minutiae-based系统时 应用系统的性能要求不要求 错误接受率很低。 最后,我们表明,匹配 可以通过结合提高性能的决定 基于互补的匹配器(minutiae-based和基于过滤器) 指纹信息。
The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining t
