Fit-sphere unwrapping and performance analysis of 3D fingerprints

Yongchang Wang, Daniel L. Lau, Laurence G. Hassebrook

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


To solve problems associated with conventional 2D fingerprint acquisition processes including skin deformations and print smearing, we developed a noncontact 3D fingerprint scanner employing structured light illumination that, in order to be backwards compatible with existing 2D fingerprint recognition systems, requires a method of unwrapping the 3D scans into 2D equivalent prints. For the latter purpose of virtually flattening a 3D print, this paper introduces a fit-sphere unwrapping algorithm. Taking advantage of detailed 3D information, the proposed method defuses the unwrapping distortion by controlling the distances between neighboring points. Experimental results will demonstrate the high quality and recognition performance of the 3D unwrapped prints versus traditionally collected 2D prints. Furthermore, by classifying the 3D database into high- and low-quality data sets, we demonstrate that the relationship between quality and recognition performance holding for conventional 2D prints is achieved for 3D unwrapped fingerprints.

Original languageEnglish
Pages (from-to)592-600
Number of pages9
JournalApplied Optics
Issue number4
StatePublished - Feb 1 2010

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering


Dive into the research topics of 'Fit-sphere unwrapping and performance analysis of 3D fingerprints'. Together they form a unique fingerprint.

Cite this