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A novel fingerprint matching algorithm based on minutiae and global statistical features

  • Peng Shi
  • , Jie Tian*
  • , Qi Su
  • , Xin Yang
  • *此作品的通讯作者
  • CAS - Institute of Automation
  • IEEE

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

The performance of Automated Fingerprint Identification System (AFIS) is highly defined by the similarity of effective features in fingerprints. Minutia is one of the most widely used local features in fingerprint matching. In this paper, we introduced two global statistical features of fingerprint image, including the mean ridge width and the normalized quality estimation of the whole image, and proposed a novel fingerprint matching algorithm based on minutiae sets combined with the global statistical features. The algorithm proposed in this paper has the advantage of both local and global features in fingerprint matching. It can improve the accuracy of similarity measure without increasing of time and memory consuming. Experimental results on FVC2004 databases showed that these improvements can make a better matching performance on public domain databases.

源语言英语
主期刊名IEEE Conference on Biometrics
主期刊副标题Theory, Applications and Systems, BTAS'07
出版商IEEE Computer Society
ISBN(印刷版)9781424415977
DOI
出版状态已出版 - 2007
已对外发布是
活动1st IEEE International Conference on Biometrics: Theory, Applications, and Systems, BTAS 2007 - Crystal City, VA, 美国
期限: 27 9月 2007 → 29 9月 2007

丛书

姓名IEEE Conference on Biometrics: Theory, Applications and Systems, BTAS'07

会议

会议1st IEEE International Conference on Biometrics: Theory, Applications, and Systems, BTAS 2007
国家/地区美国
市Crystal City, VA
时期27/09/07 → 29/09/07

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