A Robust Fingerprint Matching Approach: Growing and Fusing of Local Structures

  • Wenquan Xu
  • Xiaoguang Chen
  • Jufu Feng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)


This paper proposed a robust fingerprint matching approach based on the growing and fusing of local structures. First, we obtain candidate of minutiae triangles, the smallest local structure in our approach; and then all candidates of minutiae structures grow into larger local structures (we call growing regions) based on which we define the credibility of minutiae triangles and introduce a competition strategy; finally, growing regions compete and fuse into a much larger local structures (called fusion region). The matching score is calculated based on the evaluation of growing and fusing of local structures. Results on FVC2004 show that the proposed approach is robust to fingerprint nonlinear deformation and is efficient.


fingerprint nonlinear deformation robust local global grow fuse 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Wenquan Xu
    • 1
  • Xiaoguang Chen
    • 1
  • Jufu Feng
    • 1
  1. 1.State Key Laboratory on Machine Perception, Center for Information Science, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871P.R. China

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