Tetrahedron Based Fast 3D Fingerprint Identification Using Colored LEDs Illumination

Chenhao Lin, Ajay Kumar Pathak

Research output: Journal article publicationJournal articleAcademic researchpeer-review

29 Citations (Scopus)


IEEE Emerging 3D fingerprint recognition technologies have attracted growing attention in addressing the limitations from contact-based fingerprint acquisition and improve recognition accuracy. However, complex 3D imaging setups employed in these systems typically require structured lighting with scanners or multiple cameras which are bulky with higher cost. This paper presents a more accurate and efficient 3D fingerprint identification algorithm that uses a single 2D camera with multiple colored LED illumination. A 3D minutiae tetrahedron based algorithm is developed to more efficiently match recovered minutiae features in 3D space and address the limitations of 3D minutiae matching approach in the literature. This algorithm significantly improves the matching time to about 15 times than the state-of-art. A hierarchical tetrahedron matching scheme is also developed to further improve the matching accuracy with faster speed. The 2D images acquired to reconstruct the 3D fingerprints are also used to recover 2D minutiae and further improve matching performance for 3D fingerprints. A new two-session database consisting from 300 different clients consists of 2760 3D fingerprints reconstructed from 5520 colored 2D fingerprints is also developed and shared in public domain. Extensive experimental results presented in this paper validate our approach and demonstrate the effectiveness of proposed algorithms.
Original languageEnglish
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Publication statusAccepted/In press - 7 Nov 2017


  • 3D Fingerprint Matching
  • 3D Minutiae Tetrahedron
  • Biometrics
  • Fingerprint recognition
  • Hierarchical Tetrahedron
  • Image reconstruction
  • Imaging
  • Light emitting diodes
  • Lighting
  • Three-dimensional displays
  • Two dimensional displays

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


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