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De-identification of Facial Images by Use of Composites. *Mark E. Engelstad MD, DDS, MHI Oregon Health & Science University Dept of Oral and Maxillofacial Surgery Dept Medical Informatics & Clinical Epidemiology Genevieve B. Melton, MD, MA University of Minnesota - PowerPoint PPT Presentation
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De-identification of Facial Images by Use of Composites
*Mark E. Engelstad MD, DDS, MHIOregon Health & Science UniversityDept of Oral and Maxillofacial SurgeryDept Medical Informatics & Clinical Epidemiology
Genevieve B. Melton, MD, MAUniversity of MinnesotaInstitute for Health InformaticsDepartment of Surgery
Medbiquitous Annual Symposium, Baltimore MD May 10, 2011
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Pre-op De-identification
Original injuryPeriorbital area
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Post-op De-identification
The Questions:
Do composites de-identify faces?
Even those that are well-known to an observer?
Are facial composites realistic in appearance?
Figure 2: A comparison of two techniques for facial image de-identification. The middle image (B) is the original image. (A) black boxes only. (C) a facial composite, altered in the area of eyes and eyebrows only.
This is a PRE-operative patient
This is a POST-operative patient
I recognize this patient
Me
Faces
Subjects viewed the composite faces twice—first unaware that the faces were composites, and then primed to the presence of composites.
Subjects viewed 20 composite faces
• Subjects viewed 20 composite faces
• 10/20 had a third of a familiar face (test face)
Test Face
Test Face
Results
Subject Response Unprimed (1st Viewing)
Primed (2nd Viewing)
Facial CompositesTotal = 20
Composites of Unfamiliar
Faces Total = 10
Did Not Identify (True Neg)
100% (120/120 ) *
42% (50/120)
Identified Wrongly(False Pos)
0% (0/120) 58% (70/120)
Composites with Familiar (Test) Faces
Total = 10
Identified Correctly (True Pos)
0% (0/120) 62% (74/120)
Identified Wrongly (False Pos)
0% (0/120) 19% (23/120)
Failed to Identify (False Neg)
100% (120/120 ) *
19% (23/120)
No subjects identified test faces unless they were primed to their presence (* p < 0.001).
Results
Familiar Face Composite A Region Visible
Familiar Face Composite B Region Visible
Faces A and B Views by region (n)
42%(5/12)
79% *(19/24)
67%(24/36)
Upper
36
71% †(17/24)
38% †9/24
54%(26/48)
MidFace
48
67%(8/12)
67%16/24
67%(24/36)
Lower
36
Total Face A
63%(30/48)
Total Face B
61%(44/72)
Total Faces A and B62%
(74/120)
Total
120
Table 2: Identification of Test faces after priming--compared by facial region. Percentages of subjects who correctly identified a familiar face when regions of that face were visible in the composite image are shown (true positives). In Test Face B, a significant difference (* p<0.01) in identification rate existed between Upper Face and Midface. Test Face A Midface was recognized correctly more often than Test Face B Midface (†p<0.01)
OriginalBlack Boxes Composite, Eyes only
Making a Facial Composite
1: Photoshop
2: A Library
Step 2,3: Remove Background, Change laterality
4: Size all images to a standard (800 x1200)
5: Align the facial features
6: Create a Layer Mask
7: Use a Brush to reveal deeper layer
8: Blend the edges between the two layers
9: Correct Color Tones
Show Simulation/ Example