指纹识别中脊分岔检测的旋转不变细化算法

P. Patil, S. Suralkar, Faiyaz B. Sheikh
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引用次数: 39

摘要

在本文中,我们修改了Ahmed和Ward(2002)提出的细化算法。该算法的独特之处在于它能够将任何符号或指纹瘦到其中心线,同时注意保留符号的形状,同时保持旋转不变性。我们改进的算法还包含了一个过程,使宽度为两个像素的锯齿形对角线变细,这在“基于旋转不变规则的字符识别细化算法”中没有考虑到(Ahmed和Ward, 2002)。该算法是迭代的,并利用并行处理来加快执行速度。该系统的推理引擎中有21条规则,在每次迭代中同时应用于每个像素。该算法用于将指纹,字体和符号细化到单个像素宽度。我们还介绍了一种基于24条规则的山脊分岔检测掩码,它可以作为一种生物特征来帮助识别/认证指纹
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rotation invariant thinning algorithm to detect ridge bifurcations for fingerprint identification
In this paper we have modified the thinning algorithm proposed by Ahmed and Ward (2002). The unique feature that distinguishes the algorithm is its ability to thin any symbol or fingerprint to its central line taking care that the shape of the symbol is preserved while being rotation invariant. Our modified algorithm also incorporates a process to thin zigzag diagonal lines having a width of two pixels which was not considered in "a rotation invariant rule-based thinning algorithm for character recognition" (Ahmed and Ward, 2002). The algorithm is iterative and makes use of parallel processing to speed up execution. The system has 21 rules in its inference engine which are applied simultaneously to every pixel in each iteration. The algorithm is implemented for thinning fingerprints, fonts and symbols to a single pixel width. We also introduce a 24 rule based mask for detection of ridge bifurcations, which can be helpful for recognition/authentication of fingerprints as a biometric
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