A novel algorithm for fingerprint singular points detection based on vecrot orthogonal theory

Hang Yin, Xiaojun Jing, Songlin Sun
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引用次数: 3

Abstract

Fingerprint recognition is a widely used biometric identification mechanism. The singular points of fingerprints are important referential points for the fingerprint classification and fingerprint matching. In this paper, we propose a novel algorithm for detecting the singular points. The method is based on vector orthogonal theory and the fact that the singular points have special pattern of the orientation field. We use the same mask to detect the core points and delta points in different field. After applying the special mask, the core points and delta points will be detected in the orientation field and double orientation field respectively. To substantiate the performance of our approach, we have experimented with fvc2002 and fvc2004 database. Experimental results show that our algorithm is accurate and robust, giving better results than competing approaches.
基于矢量正交理论的指纹奇异点检测新算法
指纹识别是一种应用广泛的生物特征识别机制。指纹奇异点是指纹分类和指纹匹配的重要参考点。本文提出了一种新的奇异点检测算法。该方法基于矢量正交理论和奇异点具有特殊方向场模式的事实。我们使用相同的掩模来检测不同场的核心点和增量点。应用特殊掩模后,在方向场和双方向场中分别检测核心点和增量点。为了验证我们的方法的性能,我们对fvc2002和fvc2004数据库进行了实验。实验结果表明,该算法具有较好的鲁棒性和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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