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. 2012 Jun;25(3):347-51.
doi: 10.1007/s10278-011-9429-3.

Facial recognition software success rates for the identification of 3D surface reconstructed facial images: implications for patient privacy and security

Jan C Mazura  1 , Krishna Juluru, Joseph J Chen, Tara A Morgan, Majnu John, Eliot L Siegel
Affiliations

Facial recognition software success rates for the identification of 3D surface reconstructed facial images: implications for patient privacy and security

Jan C Mazura et al. J Digit Imaging. 2012 Jun.

Abstract

Image de-identification has focused on the removal of textual protected health information (PHI). Surface reconstructions of the face have the potential to reveal a subject's identity even when textual PHI is absent. This study assessed the ability of a computer application to match research subjects' 3D facial reconstructions with conventional photographs of their face. In a prospective study, 29 subjects underwent CT scans of the head and had frontal digital photographs of their face taken. Facial reconstructions of each CT dataset were generated on a 3D workstation. In phase 1, photographs of the 29 subjects undergoing CT scans were added to a digital directory and tested for recognition using facial recognition software. In phases 2-4, additional photographs were added in groups of 50 to increase the pool of possible matches and the test for recognition was repeated. As an internal control, photographs of all subjects were tested for recognition against an identical photograph. Of 3D reconstructions, 27.5% were matched correctly to corresponding photographs (95% upper CL, 40.1%). All study subject photographs were matched correctly to identical photographs (95% lower CL, 88.6%). Of 3D reconstructions, 96.6% were recognized simply as a face by the software (95% lower CL, 83.5%). Facial recognition software has the potential to recognize features on 3D CT surface reconstructions and match these with photographs, with implications for PHI.

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Figures

Fig. 1
Fig. 1
A digital photograph (left) and a 3D reconstructed image (right) of the same patient
Fig. 2
Fig. 2
Screen capture from Picasa in which Picasa correctly suggests that the person in the photograph and the 3D reconstructed image represent the same individual (event 3 as outlined in the text representing a correct match)
See this image and copyright information in PMC

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