Three dimensional palmprint recognition using structured light imaging

Dapeng Zhang, Lei Zhang, Nan Luo, Wei Li, Guangming Lu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

26 Citations (Scopus)


Palmprint is one of the most unique and stable biometric characteristics. Although 2D palmprint recognition can achieve high accuracy, the 2D palmprint images can be easily counterfeited and much 3D depth information is lost in the imaging process. This paper presents a new approach, 3D palmprint recognition, to exploit the 3D structural information of the palm surface. The structured-light imaging is used to acquire the 3D palmprint data, from which the features of Mean Curvature, Gauss Curvature and Surface Type (ST) are extracted. A fast feature matching and score level fusion strategy are then used to classify the input 3D palmprint data. With the established 3D palmprint database, a series of verification and identification experiments are conducted and the results show that 3D palmprint technique can achieve high recognition rate while having high anti-counterfeiting capability.
Original languageEnglish
Title of host publicationBTAS 2008 - IEEE 2nd International Conference on Biometrics
Subtitle of host publicationTheory, Applications and Systems
Publication statusPublished - 1 Dec 2008
EventBTAS 2008 - IEEE 2nd International Conference on Biometrics: Theory, Applications and Systems - Arlington, VA, United States
Duration: 29 Sep 20081 Oct 2008


ConferenceBTAS 2008 - IEEE 2nd International Conference on Biometrics: Theory, Applications and Systems
Country/TerritoryUnited States
CityArlington, VA

ASJC Scopus subject areas

  • Biotechnology

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