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Partial fingerprint matching using minutiae and ridge shape features for small fingerprint scanners

机译:使用细节和脊形特征的部分指纹匹配,适用于小型指纹扫描仪

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摘要

Currently, most mobile devices adopt very small fingerprint sensors that only capture small partial fingerprint images. Accordingly, conventional minutiae-based fingerprint matchers are not capable of providing convincing results due to the insufficiency of minutiae. To secure diverse mobile applications such as those requiring privacy protection and mobile payments, a more accurate fingerprint matcher is demanded. This manuscript proposes a new partial fingerprint-matching method incorporating new ridge shape features (RSFs) in addition to the conventional minutia features. These new RSFs represent the small ridge segments where specific edge shapes (concave and convex) are observed, and they are detectable in conventional 500 dpi images. The RSFs are effectively utilized in the proposed matching scheme which consists of minutiae matching and ridge-feature-matching stages. In the minutiae matching stage, corresponding minutia pairs are determined by comparing the local RSFs and minutiae adjacent to each minutia. During the subsequent ridge-feature-matching stage, the RSFs in the overlapped area of two images are further compared to enhance the matching accuracy. A final matching score is obtained by combining the resulting scores from the two matching stages. Various tests for partial matching were conducted on the FVC2002, FVC2004 and BERC (self-constructed) databases, and the proposed method shows significantly lower equal-error rates compared to other matching methods. The results show that the proposed method improves the accuracy of fingerprint recognition, especially for implementation in mobile devices where small fingerprint scanners are adopted. (C) 2017 Elsevier Ltd. All rights reserved.
机译:当前,大多数移动设备采用非常小的指纹传感器,仅捕获小的部分指纹图像。因此,由于细节不足,传统的基于细节的指纹匹配器不能提供令人信服的结果。为了保护多样化的移动应用程序(例如需要隐私保护和移动支付的应用程序),需要更准确的指纹匹配器。该手稿提出了一种新的部分指纹匹配方法,除了传统的细节特征外,还结合了新的脊形特征(RSF)。这些新的RSF代表观察到特定边缘形状(凹形和凸形)的小脊段,并且在传统的500 dpi图像中可以检测到它们。在提出的匹配方案中有效利用了RSF,该方案由细节匹配和脊特征匹配阶段组成。在细节匹配阶段,通过比较每个细节附近的局部RSF和细节来确定相应的细节对。在随后的山脊特征匹配阶段,将两个图像的重叠区域中的RSF进行进一步比较,以提高匹配精度。通过将来自两个匹配阶段的结果分数进行组合,可以获得最终的匹配分数。在FVC2002,FVC2004和BERC(自构造)数据库上进行了部分匹配的各种测试,与其他匹配方法相比,该方法显示出的平均错误率低得多。结果表明,该方法提高了指纹识别的准确性,特别是在采用小型指纹扫描仪的移动设备中的实现。 (C)2017 Elsevier Ltd.保留所有权利。

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