Singularity detection in fingerprint image using orientation consistency

G. C. Zacharias, P. Lal
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引用次数: 3

Abstract

In spite of the fact that a fingerprint image may suffer from problems like noises and distortions, estimating core and delta points (singular points) is crucial for most of the automatic fingerprint identification system (AFIS). Singular points have wide range of uses in AFIS which include fingerprint alignment and classification. This paper presents a simple method to locate singular points from fingerprint images using orientation consistency measure. Since consistency of the orientation field is minimum in singular regions, this method will find the local minimum to accurately detect the singular points. Core and delta points are distinguished by using the orientation field change. Experimental results show that our proposed algorithm can detect singular points effectively.
基于方向一致性的指纹图像奇异点检测
尽管指纹图像可能会受到噪声和失真等问题的影响,但对于大多数指纹自动识别系统(AFIS)来说,核心点和delta点(奇异点)的估计是至关重要的。奇异点在指纹识别系统中有着广泛的应用,包括指纹比对和分类。本文提出了一种基于方向一致性测量的指纹图像奇异点定位方法。由于方向场的一致性在奇异区域最小,因此该方法通过寻找局部最小值来精确检测奇异点。利用方向场的变化来区分核点和δ点。实验结果表明,该算法可以有效地检测到奇异点。
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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