Geographic Information Systems and
Spatial Analysis – Part 1:
Quantifying Fingerprint Patterns and
Minutiae Distributions
Ryan J. Stanley*1, Emma K. Dutton1,2, Stephen B. Taylor1,
Patrick R. Aldrich1 and Bryan E. Dutton1
1Division
2Oregon
of Natural Sciences and Mathematics
Western Oregon University
State Police, Forensic Services Division
Outline
• Background
• Methodology
• Preliminary Results
• Summary
Background: Impetus for the study
• Feb. 2009 NAS report, “Strengthening Forensic
Science in the United States: A Path Forward”
– Recommendation 3: Indicated need to improve the
scientific accuracy and reliability of forensic science
evidence.
• Sept. 2009 Awarded NIJ Grant: Fundamental
Research to Improve Understanding of the
Accuracy, Reliability, and Measurement Validity
of Forensic Science Disciplines (emphasis on
impression based evidence)
Applications of GIS
GIS: Cartography + Statistical Analysis + Database Technology
A. Example GIS Application
B. GIS Applied to Fingerprints
Customers
V
e
c
t
o
r
Core to Minutiae Distances
and Ridge Counts
Streets
Parcels
Minutiae
Elevation
R
a
s
t
e
r
Source: ESRI
Land Usage
Fingerprint Skeleton
Real World
Fingerprint Image
Geographic Information Systems and Spatial Analysis
• GIS is commonly deployed for crime pattern analysis and
emergency management
• Use as an analytical tool for fingerprint analysis is sparse to
absent in the literature
• GIS widely applied in the Geosciences for spatial analysis
including data modeling, image processing, grid algebra,
surface analysis, network analysis and visualization
• GIS extensively used in Geography as a tool for performing
statistical analysis and probability modeling
• GIS application to fingerprint analysis, identification and
pattern characterization represents an untapped resource
Methodology
• Fingerprint image acquisition and minutiae
detection
• Georeferencing and verification
• GIS data conversion and management
• Spatial analysis of ridge line and minutiae
distributions
• Statistical analysis and probability modeling
125
75
100
100 mm
0
25
50
100 mm
Y Coordinate (mm)
150
Georeferencing:
Standardized Coordinate System
0
25
50
75
100
X Coordinate (mm)
125
150
GIS Data Conversion
Fingerprint Image
100
Fingerprint Minutiae
100
100
Vectorized Ridge Lines
100
100
100
Minutiae Attribute Table
X_COORD Y_COORD MIN_DIR PT_ID MIN_TYP PRNT_TYP File_Id
100.00
100.00
180
1000
C
RS 1_87_ri
96.42
95.12
-1
2001
D
RS 1_87_ri
88.49
92.79
45
1
A
RS 1_87_ri
88.87
92.36
225
2
B
RS 1_87_ri
89.15
100.05
214
3
B
RS 1_87_ri
89.61
88.81
68
4
A
RS 1_87_ri
90.50
90.48
56
5
A
RS 1_87_ri
90.83
89.18
236
6
B
RS 1_87_ri
91.20
88.75
68
7
A
RS 1_87_ri
91.35
93.97
45
8
B
RS 1_87_ri
91.77
107.65
225
9
B
RS 1_87_ri
92.25
100.28
202
10
A
RS 1_87_ri
92.72
104.05
34
11
A
RS 1_87_ri
Oregon Fingerprint Database
Table 1. Frequency of Pattern Type by Finger and Hand
Left
Loop
Right
Loop
Double
Loop
Whorl
Whorl
Arch
Tented
Arch
TOTAL
Left Index
125
45
28
58
18
30
304
Right Index
48
110
15
78
21
36
308
Left Thumb
173
2
66
41
9
0
291
2
152
63
74
6
0
297
348
309
172
251
54
66
1200
Left
Loop
Right
Loop
Double
Loop
Whorl
Whorl
Arch
Tented
Arch
TOTAL
Left Hand
298
47
94
99
27
30
595
Right Hand
50
262
78
152
27
36
605
FINGER
Right Thumb
TOTAL
HAND
Fingerprint Skeletonization and Vectorization
Core
Coded
to Ridgeline
Delta Ridge
Attributes
Count
RidgesRidge Ending
16 - Ridge Ending
Ridge Ending - Bifurcation
Distance
11.11 mm
Line
Ridge Ending - Ridge Ending
Bifurcation - Bifurcation
Ridge Ending - Hull
Density
ridges/mm
Bifurcation 1.53
- Bifurcation
Bifurcation - Hull
Hull - Hull
TIN (Delaunay) Triangles
2
20
2
8
5
7
1. Vectorized fingerprint
5
4
3. TIN polygons
2
11
2
4
3
4
4
1
03
1
1
2 3
4
2
0 11 1
0
2
0 1 0 001
0
3
1
1
12
0 3
3
0
2
2
20 1 3
4
1
1
9
0
2
8
8
1
5
3 2
2
2
1
3
2
4
2
4
2
3
2
5 34
9
3 4
1
2
4 2
0 1
5
0
12 1
2
0
0 0
1
1
0
01
1
6
2
1
0
22
4
2
2
1
1
2
2
1 1
4
3
0
3
4
0
1
3
1
2
0
2
1
3
4
4
3
0
1
8
0
2
2
1
1 2 2
0
0
3
3
2
2 3
0
1 2
1
7
2
0
4 13
5
11
1
5
11
13
2
7
2
1
1
1
11
2
1
4
1
1
1
1
3
0
2
3
33
0
1
1
4
0
3
3
2
1
3
8
3
2
0
5
2
4
7
4
5
43
1
7
3
6
2
9
2
0
0
1
6
0
21
1
6
2
1
0
2
7
3
2
1
6
0
53
11 2 4
3
2
3
1
0
2
1
3
0
44
2
5. TIN ridge counts
2 4
3
7
2
4. TIN polylines
8
64
7
3
4
7
6
1
4
5
7
7
1
1
1
5
4 4
7
4
0
2. Minutiae
2
3
1
2
4
0
13
3 2
PRELIMINARY RESULTS:
Spatial Analysis of Minutiae
Distributions
Spatial Distribution of Minutiae
340
C. Whorls
n = 348
A. Left Slant Loops
Azimuth (deg.)
Azimuth (deg.)
0
0
350
10
20
330
340
30
320
310
300
290
70
80
% Freq.
260
2%
90
3%
250
100
110
240
290
80
% Freq.
230
190 180 170
160
B. Right Slant Loops
340
0
10
340
20
320
310
260
300
290
70
280
80
% Freq.
1%
2%
90
3%
250
100
110
240
120
230
130
220
140
210
150
160
0
10
120
230
130
220
140
150
160
n = 66
Azimuth (deg.)
20
340
80
% Freq.
2%
90
3%
250
100
110
240
120
230
130
140
210
150
160
20
30
40
50
300
280
220
10
310
70
1%
0
320
290
270
350
330
60
190 180 170
190 180 170
F. Tented Arches
50
200
100
110
40
0%
90
3%
250
30
260
2%
240
n = 172
300
60
270
350
1%
210
310
50
190 180 170
0%
200
320
40
200
270
160
330
30
0%
80
% Freq.
Azimuth (deg.)
330
260
190 180 170
D. Double Loop Whorls
Azimuth (deg.)
350
60
150
200
n = 309
50
70
140
210
40
290
130
220
30
280
120
150
200
100
110
140
210
90
3%
240
130
220
2%
250
120
230
70
280
260
20
300
60
1%
10
310
50
0%
0
320
40
270
350
330
30
300
280
1%
340
20
310
60
0%
10
320
50
270
350
n = 54
Azimuth (deg.)
330
40
E. Arches
n = 251
60
290
70
280
80
% Freq.
270
0%
260
1%
2%
90
3%
250
100
110
240
120
230
130
220
140
210
150
200
190 180 170
160
B. Right Slant Loops
120
4
-0
.4
.1
-0
.0
76
-0
0.
14
1
0.
07
6
1
03
6
1
1
110
120
n = 66
80
90
100
110
120
110
100
F. Tented Arches
n = 172
110
100
0.
120
100
90
01
0
120
110
90
80
90
n = 54
100
100
80
80
90
100
110
120
90
D. Double Loop Whorls
n = 309
80
0.436
80
80
120
0.
110
0.14
120
100
E. Arches
0.076
90
100
90
80
90
0.036
110
120
n = 251
110
120
110
100
90
80
80
0.
0
C. Whorls
n = 348
A. Left Slant Loops
.0
36
0.01
-0
-0
.0
1
0.001
01
0
36
Average Minutiae Density
(Avg. Number Minutiae / Sq. mm)
0
2-mm Grid Cell Minutiae Density
All Minutiae
80
90
100
110
120
80
90
100
110
120
B. Right Slant Loops
110
D. Double Loop Whorls
120
120
4
-0
.4
.1
-0
.0
76
-0
0.
14
1
0.
07
6
1
03
6
1
1
110
120
n = 66
80
90
100
110
120
100
110
100
F. Tented Arches
n = 172
90
100
01
0
120
100
80
90
90
n = 54
100
90
110
120
110
100
90
80
80
80
0.436
80
80
n = 309
0.
120
0.
110
0.14
120
100
E. Arches
0.076
90
100
90
80
90
0.036
110
120
n = 251
110
120
110
100
90
80
80
0.
0
C. Whorls
n = 348
A. Left Slant Loops
.0
36
0.01
-0
-0
.0
1
0.001
01
0
36
Average Minutiae Density
(Avg. Number Minutiae / Sq. mm)
0
2-mm Grid Cell Minutiae Density
Ridge Endings
80
90
100
110
120
80
90
100
110
120
110
B. Right Slant Loops
120
D. Double Loop Whorls
120
4
-0
.4
.1
-0
.0
76
-0
0.
14
1
0.
07
6
1
03
6
1
1
110
120
n = 66
80
90
100
110
120
120
100
F. Tented Arches
n = 172
100
110
01
0
110
110
90
100
n = 54
100
100
80
90
90
0.436
90
90
110
120
110
100
90
80
80
80
0.14
80
80
n = 309
0.
100
0.076
120
90
E. Arches
0.
120
100
90
80
80
0.036
120
n = 251
110
120
110
100
80
90
0.
0
C. Whorls
n = 348
A. Left Slant Loops
.0
36
0.01
-0
-0
.0
1
0.001
01
0
36
Average Minutiae Density
(Avg. Number Minutiae / Sq. mm)
0
2-mm Grid Cell Minutiae Density
Bifurcations
80
90
100
110
120
80
90
100
110
120
Minutiae / Ridge Frequency Ratio
• Compared minutiae / ridge
count ratios above and below
the core for 188 vectorized
fingerprints (all pattern types)
Above Core
- Minutiae: 33
- Ridge Lines: 81
- Minutiae/Ridge Ratio: 0.41
• Paired t-test:
– t = -24.525, df = 187
– mean difference = -0.19
– p-value < 2.2e-16
• Difference in minutiae / ridge
ratios above and below core is
significant with a p < 2.2e-16
Below Core
- Minutiae: 63
- Ridge Lines: 100
- Minutiae/Ridge Ratio: 0.63
Summary
• Fingerprint analysis is based on spatial associations
between minutiae and ridge lines, so GIS-based tools for
spatial analysis are a natural extension.
• The project-related GIS tools and preliminary results offer
promising contributions to the advancement of fingerprint
analysis and forensic science in the near future.
• Other fingerprint characterization methods not presented:
– Thiessen polygons
– Ridge Density Maps
– Dart Board Minutiae Density Maps
– Fingerprint Geometry
– Monte Carlo Minutiae Simulation
Acknowledgments
• National Institute of Justice (Grant Award #
2009-DN-BX-K228)
• Western Oregon University
• Oregon State Police, Forensic Services
Division and ID Services Division
This project was supported by Award No. 2009-DN-BX-K228 awarded by the National Institute of
Justice, Office of Justice programs, U.S. Department of Justice. The opinions, findings, and
conclusions or recommendations expressed in this publication/program/exhibition are those of the
author(s) and do not necessarily reflect those of the Department of Justice.