Fingerprint minutiae matching using the adjacent feature vector

  • Authors:
  • Xifeng Tong;Jianhua Huang;Xianglong Tang;Daming Shi

  • Affiliations:
  • School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, P.R. China and Daqing Petroleum Institute, Daqing, P.R. China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, P.R. China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, P.R. China;School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2005

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Abstract

Minutiae matching is the most popular approach to fingerprint verification. In this paper, we propose a novel fingerprint feature named the adjacent feature vector (AFV) for fingerprint matching. An AFV consists of four adjacent relative orientations and six ridge counts of a minutia. Given a fingerprint image, the optimal matching score is computed in three stages: (1) minutiae candidate pairs searching based on AFVs; (2) coordinate transform for image rotation and translation; and (3) transformed minutiae matching to get matching score. The experimental results show that the proposed method provides a good trade-off between speed and accuracy.