1. Visual Processing in Fingerprint Experts and Novices
Tom Busey
Indiana University, Bloomington
John Vanderkolk
Indiana State Police, Fort Wayne
Expertise with fingerprint examiners was tested in behavioral and EEG studies. Experts show greater tolerance for noise, are unaffected by longer memory delays, and show evidence of configural processing. This last finding was confirmed in an EEG study where experts show a reliable delay of the N170 component when fingerprints were inverted, while novices did not. Configural processing may be one element that underlies perceptual expertise.

2. How Do Experts Make Identifications?
Easy Match
Hard Match

3. How Do Experts Make Misidentifications?
The Madrid Bombing Fingerprints:

4. Testing Fingerprint Expertise: X-AB Sequential Matching Task
example stimulus pairs:

5. Image Degradations at Test

6. Partial Masking Semi-Transparent Masks Fingerprint Partially Masked
original
inverse
Summation
Recovers Original
Fingerprint
Semi-Transparent
Masks
Fingerprint
Partially Masked
Fingerprints

7. Partial Images in Noise
Behavioral Data
Full Images
Partial Images
Full Images in Noise
Partial Images in Noise
Experts: No effect of delay, interaction between noise and partial masking.

8. Evidence for Configural Processing
Full Image (Both Halves)
Partial Image (One Half)
info from first half?
yes
(db) no
(1-db)
info from second half?
info from first half?
yes
(db) no
(1-db)
yes
(do) no
(1-do)
info from guessing?
info from guessing?
yes
(g) no
(1-g)
yes
(g) no
(1-g)
Correct Decision
Wrong Decision
Correct Decision
Wrong Decision
Question: What is the relation between db and do?
if db = do : One half doesn't influence information acquired from other half
if db < do : Get less information from one half when second is present
if db > do : Get more information from one half when second is present
(consistent with configural or gestalt processing)

9. Multinomial Modeling Conclusions
To test for configural processing, fit a reduced model with db = do. If we can reject this model, then we know that the two are not the same. Fit the full model to see the relation between db and do.
Experts:
No noise: we reject reduced model, so db and do are significantly different
Full model: db = .841, do = wrong direction for configural processing
In noise: we reject reduced model, so db and do are significantly different
Full model: db = .50, do = Consistent with configural processing
Novices:
No noise: we reject reduced model, so db and do are significantly different
Full model: db = .40, do = wrong direction for configural processing
In noise: we can't reject reduced model, so db and do are not significantly different
Full model: db = .19, do = No evidence for configural processing

10. Configural Processing in Faces: The ‘Thatcher Illusion’
Features are perceived individually, image looks ok.
Features are perceived in context, image looks grotesque.
(Thomson, 1980)

11. EEG and Configural Processing
Faces produce a strong component over the right hemisphere at about 170 ms after stimulus onset, which is called the N170. Inverted faces cause a delay of ms in the N170.
Trained objects (Greebles) show a delay in the N170 component with inversion, but only in the left hemisphere (channel T5).
Data from Rossion, Gauthier, Tarr, Despland, Bruyer, Linotte & Crommelinck (2000)
fMRI studies show IT is active whether attending to faces or not (Tarr)
No effect of familiarity (Bentin & Deouell, 2000)
target status: Is the face-sensitive N170 the only ERP not affected by selective attention? (Caquil, Edmonds, & Taylor, 2000)
Appears to be feed-forward perceptual processing of faces or other face-like stimuli
Coupled with behavioral data suggesting configural processing with faces, an advanced N170 to an upright stimulus suggests that the N170 latency differences indicate configural processing.
Data from Rossion, Gauthier, Goffaux, Tarr & Crommelinck (2002)

12. An Obvious Experiment:
Show upright and inverted fingerprints to Fingerprint examiners and novices. If experts process fingerprints configurally, we should see a delayed N170 to inverted fingerprints.
fMRI studies show IT is active whether attending to faces or not (Tarr)
No effect of familiarity (Bentin & Deouell, 2000)
target status: Is the face-sensitive N170 the only ERP not affected by selective attention? (Caquil, Edmonds, & Taylor, 2000)
Appears to be feed-forward perceptual processing of faces or other face-like stimuli
Also test faces to replicate the face inversion effect in our subjects. Test both identification and categorization tasks.

13. Expert Data- Identification Task
Electrode T6
Upright Fingerprint
Inverted Fingerprint
Upright Face
Inverted Face
Delayed
Amplitude (µV)
Time (ms)
Experts: delayed N170 with
inverted fingerprints and inverted
faces.
Delayed

14. Novice Data- Identification Task
Electrode T6
Upright Fingerprint
Inverted Fingerprint
Upright Face
Inverted Face
No Delay
Amplitude (µV)
Time (ms)
Novices: no delayed N170 with
inverted fingerprints, but see with
faces.
Delayed

15. Expert Data- Categorization Task
Electrode T6
Upright Fingerprint
Inverted Fingerprint
Upright Face
Inverted Face
Delayed
Amplitude (µV)
Time (ms)
Experts: delayed N170 with
inverted fingerprints and inverted
faces.
Delayed

16. Novice Data- Categorization Task
Electrode T6
Upright Fingerprint
Inverted Fingerprint
Upright Face
Inverted Face
No Delay
Amplitude (µV)
Time (ms)
Novices: no delayed N170 with
inverted fingerprints, but see with
faces.
Delayed

17. Summary and Conclusions
Fingerprint experts demonstrate strong performance in an X-AB matching task, robustness to noise and evidence for configural processing when stimuli are presented in noise. This latter finding was confirmed using upright and inverted fingerprints in an EEG experiment. Experts showed a delayed N170 component for inverted fingerprints in the same channel that they show a delayed N170 for inverted faces. Thus they appear to be processing upright fingerprints in part using configural or holistic processing, which stresses relational information and implies dependencies between individual features. In the case of fingerprints, this may come from idiosyncratic feature elements instead of well-defined features such as eyes and mouths.