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基于加权平均梯度方向场和改进Poincare Index的指纹奇异点检测算法

Fingerprint singular points detection based on both weighted averaging gradient directional field and improved Poincare Index
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摘要 针对指纹图像具有局部平行性和渐变性以及邻域的脊线方向相关性高的特点,提出了一种基于加权平均梯度的指纹方向场算法。改进了传统的PoincareIndex指纹奇异点检测算法。实验证明,在采用加权平均梯度算法获取的方向场上利用改进的PoincareIndex算法可实现对低质量指纹图像的奇异点的准确提取。 Because the fingerprint is characterized by the local parallel, gradual change and high correlation of neighborhoods, a gradient based weighted averaging algorithm was proposed. The conventional poincare index algorithm for detecting the singular points of fingerprint was improved. The experimental results suggest that the improved poincare index algorithm on the weighted averaging gradient directional field can accurately detect the singular points of fingerprint.
作者 付佳 潘伟 郝重阳
机构地区 西北工业大学电子信息学院 中国空间技术研究院
出处 《计算机应用》 CSCD 北大核心 2007年第10期2563-2565,共3页 journal of Computer Applications
关键词 指纹 奇异点 加权平均梯度方向场 POINCARE INDEX fingerprint singular point weighted averaging gradient directional field Poincare Index
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献7

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二级参考文献11

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计算机应用
2007年 第10期

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