Biometric identification using knee X-rays

Lior Shamir, Shari Ling, Salim Rahimi, Luigi Ferrucci, Ilya G. Goldberg

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Identification of people often makes use of unique features of the face, fingerprints and retina. Beyond this, a similar identifying process can be applied to internal parts of the body that are not visible to the unaided eye. Here we show that knee X-rays can be used for the identification of individual persons. The image analysis method is based on the wnd-charm algorithm, which has been found effective for the diagnosis of clinical conditions of knee joints. Experimental results show that the rank-10 identification accuracy using a dataset of 425 individuals is ~excl;«56%, and the rank-1 accuracy is ~excl;«34%. The dataset contained knee X-rays taken several years apart from each other, showing that the identifiable features correspond to specific persons, rather than the present clinical condition of the joint.

Original languageEnglish (US)
Pages (from-to)365-370
Number of pages6
JournalInternational Journal of Biometrics
Volume1
Issue number3
DOIs
StatePublished - Mar 2009
Externally publishedYes

Keywords

  • Biometrics
  • Bone
  • Joint
  • Radiography
  • X-ray

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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