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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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【作者】 付佳潘伟郝重阳

【Author】 FU Jia1,PAN Wei2,HAO Chong-yang1 1.School of Electronic Enqineering,Northwestern Polytechnical University,Xi’an Shaanxi 710072,China;2.China Cademy of Space Technology,Beijing 100086,China

【机构】 西北工业大学电子信息学院中国空间技术研究院西北工业大学电子信息学院 西安710072北京100086西安710072

【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。

【Abstract】 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.

  • 【文献出处】 计算机应用 ,Journal of Computer Applications , 编辑部邮箱 ,2007年10期
  • 【分类号】TP391.41
  • 【被引频次】3
  • 【下载频次】272
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