东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (6): 798-801.DOI: -

• 论著 • 上一篇    下一篇

指纹核心点的位置确定及其方向计算

毛克明;王国仁;于长永;金艳;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-06-15 发布日期:2013-06-22
  • 通讯作者: Mao, K.-M.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60573089,60773219);;

Fingerprint core point localization and its orientation computation

Mao, Ke-Ming (1); Wang, Guo-Ren (1); Yu, Chang-Yong (1); Jin, Yan (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-06-15 Published:2013-06-22
  • Contact: Mao, K.-M.
  • About author:-
  • Supported by:
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摘要: 核心点作为指纹的一个基本特征,在指纹匹配和分类中起着重要作用.应用机器学习方法区分核心点区域与非核心点区域.核心点区域与非核心点区域的脊线局部方向分布可用来构造训练数据,并用多尺度SVM方法得到训练模型,并由相应的模型估计出核心点的准确位置.定义了核心点的方向,并利用一种启发式方法来计算.实验表明,该方法可以准确有效地确定核心点的位置和方向,并提高指纹匹配的性能.

关键词: 指纹, 核心点, 位置, 方向, 支持向量机

Abstract: Core point, as an essential feature of fingerprint, plays an important role in fingerprint matching/classification, where the core point region is distinguished from non-core point region by the machine learning method, and their ridge orientation distributions can be used to form training data. Then, the multi-resolution SVM method is used to gain a training model so as to predict accurately the position of core point by corresponding models. Moreover, the orientation of core point is defined reasonably and a heuristic method is devised to compute it. Experimental results showed that the proposed method can localize the position of core point and compute its orientation with high accuracy and efficiency.

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