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Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 53
FINGERPRINTS SIMILARITIES BETWEEN SIBLINGS AND
NON-RELATED PEOPLE IN LAGOS, NIGERIA
IROANYA, O.O.*, UMELUE, V.I. AND EGWUATU, T.F.
Department of Cell Biology and Genetics, University of Lagos, Akoka Yaba, Lagos
ABSTRACT
Purpose: Fingerprint impressions provide powerful means of personal identification. This study was carried out
to determine if siblings have similar fingerprint patterns, degree of similarities and to determine if these
similarities can be attributed to the family of the siblings.
Principal methodologies: A total of 74 individuals randomly picked from different families residing in Lagos,
Nigeria participated in this study. Fingerprint impressions were taken using Persona fingerprint scanner. The
level of similarity and percentage similarity was assessed using the principle of match and mismatch.
Key findings: Of seventeen sets of siblings, fourteen showed a percentage similarity of 50% and above, while
three showed a percentage similarity of 40% and below. This clearly suggests that siblings have a percentage
similarity between their fingerprint pattern types. Statistical results showed that the loop fingerprint pattern was
the most prevalent both in siblings and non-siblings at a frequency of 56.76% and 62.5%, respectively. The most
prevalent ridge pattern was ulnar loop with a frequency of 57.06% and 60.75% in the siblings and non-siblings
respectively.
Conclusion: This study showed that siblings’ fingerprint pattern had high percentage similarity, hence, the need
to use automated fingerprint system or DNA analysis in verifying or establishing identity during criminal
investigations.
Keywords: Fingerprint; Siblings; Ridge pattern; Ulnar loop; Percentage similarity; Criminal investigations.
*Correspondence: oiroanya@unilag.edu.ng
INTRODUCTION
Fingerprints are unique patterns made by friction
ridges (raised) and furrows (recessed), which appear
on the pads of the fingers and thumbs. A fingerprint
is highly individualistic and forms the basis for
personal identification in forensic examination [1].
Fingerprints and finger marks combine to provide the
most powerful means of personal identification. The
basic patterns of fingerprints are loops, whorls and
arches that can be found in fingerprints. The arches
can be either plain or tented, and the whorls can be
classified as central pocket, lateral pocket, twins and
accidentals [2]. Slatis et al. [3] reported that as the
proportion of whorls among the parent increases, the
proportion of children with whorls also increases.
Cho [4] discovered that whorls (56.7%) were more
abundant than loops (42.6%) in Australian Aborigine
males of the Northern Territory of Australia. The
females exhibited a higher frequency of loops
(47.0%) and lower frequency of whorls (51.2%)
compared to the males. Males have a higher
incidence of whorls and females have a higher
incidence of loops [5]. Kanchan and Chattopadhyay
[6] reported that the distribution of fingerprint
patterns was similar in their subjects and thus did not
establish any gender-based differences.
The Dermatoglyphic science is based on
two major facts; first, the ridges are slightly different
for different fingers and no two persons, not even
monozygotic twins, show exactly similar fingerprint
patterns, and second, the ridges are permanent
throughout life and they survive superficial injuries
and also environmental changes after the 21st week
inter-uterine life [7]. Dermatoglyphics are constant
and individualistic and form the most reliable criteria
for identification [6].
Fingerprints collected from crime scenes
typically contain less information than fingerprints
collected under controlled conditions. Specifically,
they are often noisy and distorted and may contain
only a portion of the total fingerprint area [8]. The
performance of an automatic fingerprint
authentication system relies heavily on the quality of
the captured fingerprint images [9]. Due to the
complexity, uniqueness, and stability of the papillary
ridge patterns, fingerprints formed through papillary
ridges have been and still are considered the best
reference for personal identification in forensic
science [10].
The fingerprints encode the presence of 2D
(two dimension) structural fragments in a molecule,
and the similarity between a pair of molecules is a
function of the number of fragments that they have in
common [11]. Human identification by fingerprints
is based on the fundamental premise that ridge
patterns from distinct fingers are different
(uniqueness) and a fingerprint pattern does not
change over time (persistence) [12].Fingerprint
identification and classification has been extensively
researched in the literature [13] however there is
paucity of data on research works that studied the
fingerprints similarities between siblings and non-
related population in Lagos, Nigeria.
The aim of this study was to determine the
similarities between fingerprints of siblings and also
between fingerprints of non-siblings by comparison
using the principle of match and mismatch.
Iroanya et al. (2020); Fingerprints similarities between siblings
Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 54
MATERIALS AND METHODS
Materials used for the study
Materials used for the study were Digital Persona
fingerprint scanner and Compaq Presario laptop. The
following software were used: Digital Persona
diagnostic utility and Griaule fingerprint software.
Ethical clearance
Ethical clearance was obtained from College of
Medicine, University of Lagos Health Research
Ethics Committee (HREC/15/04/2015).This was
obtained to ensure that the ethics that govern how
scientific research is performed at the University of
Lagos, Nigeria.
Sample size determination
This study was carried out in Lagos, Nigeria from
April 20th to May 30th, 2018. Fingerprint impressions
of two (2) siblings either male or female with no age
limitation from seventeen (17) families and forty (40)
non-siblings were taken. Fingerprint impressions
were therefore taken from 34 siblings and 40 non-
siblings making a total of 74 individuals. Sample size
was determined according to the method described
by Kish [14].
Sample collection and processing
For each individual, the ten (10) fingerprint
impressions were taken using the Digital Persona
fingerprint recognition system. This was done by
placing each of the individual’s finger on the
fingerprint scanner so as to transfer the fingerprint
impression to the laptop. The fingerprint impressions
of each subject were saved on the laptop with the
following necessary details: full name and the finger
from which the fingerprint was extracted. Plate 1
shows how each subject’s fingerprint impression was
taken using a fingerprint scanner and a laptop.
Plate 1: Extraction of fingerprint from the thumb
finger
Statistical analysis
The fingerprint impressions of the siblings taken
were analysed using the principle of match and
mismatch. Every match between two fingerprint
pattern types was recorded as 1 and every mismatch
was recorded as 0. At the end of the analysis, the
figures of the match and mismatch were added up to
produce the level of similarity.
All numerical and fingerprint data was
subjected to statistical and fingerprints software
analyses using Statistical Package for the Social
Sciences (SPSS) 23.0 and Griaule Fingerprint SDK
4.2 software to draw a comparison between the
siblings and non-siblings’ fingerprints.
RESULTS
Table 1: Frequency of the fingerprint pattern in the sampled population
Whorl
Arch
Loop
Siblings (N=340)
106 (31.18%)
41 (12.06%)
193 (56.76%)
Non-siblings (N=400)
102 (25.5%)
48 (12%)
250 (62.5%)
Iroanya et al. (2020); Fingerprints similarities between siblings
Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 55
Keys:
PA= Plain arch
CPLW = Central pocket loop whorl
W = Whorl
UL= Ulnar loop
DLW = Double loop whorl
AW = Accidental whorl
TA = Tented arch
RL= Radial loop
Table 2a: The ten digits showing the fingerprint pattern types between siblings
Siblings
Right
Thumb
Right
Index
Right
Middle
Right
Ring
Right
Little
Left
Thumb
Left
Index
Left
Middle
Left
Ring
Left
Little
A1
W
W
W
W
UL
UL
W
CPLW
W
W
A2
W
RL
UL
UL
W
W
TA
UL
UL
UL
B1
W
DLW
CPLW
W
UL
W
W
UL
UL
UL
B2
W
W
UL
W
UL
CPLW
W
DLW
UL
UL
C1
UL
UL
UL
UL
UL
RL
RL
UL
UL
UL
C2
RL
UL
UL
UL
UL
RL
TA
UL
UL
UL
D1
W
UL
UL
UL
UL
W
UL
UL
UL
UL
D2
DLW
UL
UL
UL
UL
UL
PA
PA
UL
UL
E1
DLW
W
UL
W
UL
UL
W
W
CPLW
UL
E2
DLW
PA
UL
UL
W
UL
PA
UL
UL
UL
F1
UL
UL
UL
W
UL
UL
UL
UL
UL
W
F2
UL
UL
UL
DLW
RL
UL
UL
UL
DLW
W
G1
UL
UL
UL
W
UL
W
TA
UL
CPLW
UL
G2
DLW
W
UL
W
UL
DLW
W
UL
W
UL
H1
UL
DLW
UL
UL
UL
UL
W
UL
UL
UL
H2
W
W
UL
UL
UL
TA
TA
UL
UL
UL
I1
W
RL
UL
UL
UL
W
UL
UL
UL
UL
I2
AW
PA
PA
TA
UL
PA
PA
PA
PA
UL
J1
UL
UL
UL
UL
UL
UL
UL
UL
UL
UL
J2
UL
UL
UL
UL
UL
UL
UL
UL
UL
UL
K1
W
W
W
W
W
DLW
DLW
DLW
W
UL
K2
W
W
UL
W
UL
W
W
W
AW
UL
L1
W
W
W
AW
UL
DLW
CPLW
AW
UL
AW
L2
UL
W
UL
W
UL
UL
W
UL
W
W
M1
DLW
UL
UL
UL
UL
UL
UL
UL
W
UL
M2
UL
UL
UL
W
UL
UL
UL
UL
W
UL
N1
PA
PA
TA
UL
PA
PA
TA
PA
TA
PA
N2
PA
PA
PA
UL
PA
PA
PA
PA
UL
PA
O1
W
RL
UL
UL
UL
UL
DLW
UL
UL
UL
O2
DLW
UL
UL
UL
UL
DLW
UL
UL
UL
UL
P1
DLW
UL
UL
W
UL
AW
UL
UL
UL
UL
P2
UL
UL
UL
UL
UL
UL
UL
UL
UL
UL
Q1
PA
PA
PA
UL
UL
PA
PA
PA
UL
UL
Q2
PA
RL
UL
UL
UL
PA
CPLW
UL
UL
UL
Iroanya et al. (2020); Fingerprints similarities between siblings
Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 56
Table 2b: The ten digits showing the percentage similarity
Family
Level of Similarity
Percentage Similarity (%)
A
1
10
B
7
70
C
9
90
D
7
70
E
4
40
F
9
90
G
7
70
H
7
70
I
3
30
J
10
100
K
8
80
L
5
50
M
8
80
N
9
90
O
8
80
P
7
70
Q
6
60
Table 3a: Frequency and prevalence of the fingerprint pattern types on the right hand of siblings
Fingerprint
pattern
Frequency (%)
Right thumb
Right index
Right middle
Right ring
Right little
Arch
Loop
Whorl
Total
4 (11.77)
11 (32.35)
19 (55.88)
34 (100)
5 (14.71)
18 (52.94)
11 (32.35)
34 (100)
4 (11.77)
26 (76.46)
4 (11.77)
34 (100)
1 (2.94)
19 (55.88)
14 (41.18)
34 (100)
2 (5.88)
29 (85.30)
3 (8.82)
34 (100)
Table 3b: Frequency and prevalence of the fingerprint pattern types on the left hand of siblings
Fingerprint
pattern
Frequency (%)
Left thumb
Left index
Left middle
Left ring
Left little
Arch
Loop
Whorl
Total
6 (17.65)
16 (47.06)
12 (35.29)
34 (100)
10 (29.42)
12 (35.29)
12 (35.29)
34 (100)
5 (14.71)
23 (67.64)
6 (17.65)
34 (100)
2 (5.88)
22 (64.71)
10 (29.41)
34 (100)
2 (5.88)
27 (79.41)
5 (14.71)
34 (100)
The fingerprints of the non-siblings were analysed and classified into their appropriate fingerprint pattern types
(Table 4).
Iroanya et al. (2020); Fingerprints similarities between siblings
Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 57
Table 4: Ten digits showing the fingerprint pattern types for non-siblings
S/N
Right
Thumb
Right
Index
Right
Middle
Right
Ring
Right
Little
Left Thumb
Left
Index
Left
Middle
Left
Ring
Left Little
1
W
RL
UL
UL
UL
W
RL
UL
UL
UL
2
UL
W
UL
UL
UL
UL
W
UL
UL
UL
3
PA
TA
PA
UL
UL
PA
PA
PA
RL
PA
4
W
CPLW
W
W
UL
UL
CPLW
DLW
DLW
UL
5
W
W
W
CPLW
UL
DLW
W
W
W
UL
6
PA
UL
TA
UL
UL
PA
PA
UL
UL
UL
7
UL
UL
UL
UL
UL
PA
UL
UL
UL
UL
8
PA
PA
PA
PA
TA
PA
PA
PA
PA
TA
9
UL
UL
UL
UL
DLW
UL
UL
UL
UL
UL
10
DLW
UL
UL
UL
UL
UL
CPLW
UL
UL
UL
11
W
W
UL
UL
UL
PA
W
UL
W
UL
12
UL
UL
UL
UL
UL
UL
UL
UL
UL
UL
13
UL
UL
UL
UL
UL
UL
UL
UL
UL
UL
14
UL
W
UL
UL
UL
UL
W
UL
UL
UL
15
W
UL
UL
W
UL
UL
UL
UL
W
UL
16
W
UL
UL
UL
UL
W
UL
UL
UL
UL
17
W
UL
UL
W
W
DLW
UL
UL
W
W
18
DLW
W
W
DLW
UL
DLW
DLW
W
W
UL
19
UL
UL
UL
UL
UL
UL
UL
UL
UL
UL
20
UL
DLW
W
UL
UL
DLW
DLW
W
W
UL
21
W
PA
UL
UL
UL
DLW
UL
UL
UL
UL
22
W
RL
UL
UL
UL
W
UL
UL
W
UL
23
UL
UL
UL
UL
UL
UL
UL
UL
W
UL
24
PA
UL
UL
W
W
PA
UL
UL
W
W
25
PA
TA
PA
UL
UL
PA
PA
TA
TA
UL
26
DLW
W
UL
W
UL
UL
UL
DLW
UL
UL
27
PA
TA
UL
UL
UL
UL
TA
UL
UL
UL
28
DLW
UL
UL
W
UL
W
PA
UL
W
DLW
29
UL
RL
UL
UL
UL
UL
UL
UL
UL
UL
30
W
W
W
W
W
W
W
W
W
UL
31
W
W
UL
UL
UL
W
W
W
W
W
32
UL
UL
UL
UL
UL
UL
UL
UL
UL
UL
33
W
W
UL
UL
UL
UL
UL
UL
UL
UL
34
UL
UL
UL
UL
UL
UL
UL
UL
UL
UL
35
W
UL
UL
UL
UL
DLW
RL
UL
DLW
UL
36
PA
PA
PA
TA
UL
UL
PA
UL
UL
UL
37
UL
UL
PA
UL
UL
PA
PA
PA
UL
UL
38
UL
UL
UL
UL
UL
UL
UL
UL
UL
RL
39
UL
UL
UL
UL
UL
UL
PA
PA
UL
UL
40
DLW
W
W
W
W
DLW
W
W
W
UL
Iroanya et al. (2020); Fingerprints similarities between siblings
Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 58
Table 5a: Frequency and prevalence of the fingerprint pattern types on the right hand of non- siblings
Fingerprint
pattern
Frequency (%)
Right thumb
Right index
Right middle
Right ring
Right little
Arch
Loop
Whorl
Total
7 (17.5)
15 (37.5)
18 (45)
40 (100)
6 (15)
22 (55)
12 (30)
40 (100)
6 (15)
28 (70)
6 (15)
40 (100)
2 (5)
28 (70)
10 (25)
40 (100)
1 (2.5)
34 (85)
5 (12.5)
40 (100)
Table 5b: Frequency and prevalence of the fingerprint pattern types on the left hand of non-siblings
Fingerprint
pattern
Frequency (%)
Left thumb
Left index
Left middle
Left ring
Left little
Arch
Loop
Whorl
Total
8 (20)
19 (47.5)
13 (32.5)
40 (100)
9 (22.5)
19 (47.5)
12 (30)
40 (100)
5 (12.5)
27 (67.5)
8 (20)
40 (100)
2 (5)
23 (57.5)
15 (37.5)
40 (100)
2 (5)
34 (85)
4 (10)
40 (100)
Table 6: Frequency of the ridge pattern distribution of siblings
Fingerprint pattern
Frequency
Percentage
Cumulative percentage
Central pocket loop whorl
Double loop whorl
Accidental whorl
Whorl
Ulnar loop
Radial loop
Plain arch
Tented arch
Total
7
19
6
64
194
9
32
9
340
2.06
5.59
1.76
18.82
57.06
2.65
9.41
2.65
100
2.06
7.65
9.41
28.23
85.29
87.94
97.35
100
Table 7: Frequency of ridge pattern distribution of non-siblings
Fingerprint pattern
Frequency
Percentage
Cumulative percentage
Central pocket loop whorl
Double loop whorl
Accidental whorl
Whorl
Ulnar loop
Radial loop
Plain arch
Tented arch
Total
4
22
0
76
243
7
38
10
400
1
5.5
0
19
60.75
1.75
9.5
2.5
100
1
6.5
6.5
25.5
86.25
88
97.5
100
Table 8a: Prevalence of the fingerprint pattern type on each digit of the siblings
Hand
Thumb
Index
Middle
Ring
Little
Right hand
W
(55.88 %)
L
(52.94 %)
L
(76.46 %)
L
(55.88 %)
L
(85.30 %)
Left hand
L
(47.06 %)
L/W
(35.29 %)
L
(67.64 %)
L
(64.71 %)
L
(79.41 %)
*L represents loop and W represents whorl.
Iroanya et al. (2020); Fingerprints similarities between siblings
Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 59
Table 8b: Prevalence of the fingerprint pattern type on each digit of the non-siblings
Hand
Thumb
Index
Middle
Ring
Little
Right hand
W
(45 %)
L
(55 %)
L
(70 %)
L
(70 %)
L
(85 %)
Left hand
L
(47.5 %)
L
(47.5 %)
L
(67.5%)
L
(57.5%)
L
(85%)
*L represents loop and W represents whorl.
Table 1 shows the frequency distribution of the
fingerprint patterns in the sampled population. The
loop fingerprint pattern had the highest frequency of
193 (56.76%) and 250 (62.5%) in the siblings and
non-siblings respectively, with the non-siblings
having a higher percentage. The whorl fingerprint
pattern had the second highest frequency of 106
(31.18%) and 102 (25.5%) in the siblings and non-
siblings respectively, with the siblings having a
higher percentage. The arch fingerprint pattern had
the lowest frequency of 41 (12.06%) and 48 (12%) in
the siblings and non-siblings respectively, with the
non-siblings having a higher percentage. Therefore,
the non-siblings had a higher percentage of the loop
and arch fingerprint patterns, while the siblings had a
higher percentage of the whorl fingerprint pattern.
Comparison was carried out between the two siblings
of each family using fingerprint impressions of each
individual’s ten digits to determine the percentage
similarities of the fingerprint patterns. Table 2a
shows the ten digits showing the fingerprint pattern
types between the siblings.
Table 2b shows the percentage similarity of
the fingerprint patterns of siblings. The average
percentage similarity of the siblings was 67.65%.
The study also revealed that 14 out of 17 sets of
siblings showed a percentage of 50 and above while
3 out of 17 showed a percentage of 40 and below.
Therefore, it was shown that siblings have high
percentage similarities between their fingerprints.
For each of the digits, the most predominant
of the fingerprint patterns was assessed (Tables 3a
and 3b) to show the prevalence of the fingerprint
patterns on the ten digits among siblings. For the
right thumb finger, the whorl fingerprint pattern was
most the prevalent with a frequency of 19 (55.8%)
while arch had the least with a frequency of 4
(11.77%). The right index finger had more of the
loop fingerprint pattern with a frequency of 18
(52.94%) compared to the others (whorl and arch).
For the right middle finger, the loop fingerprint
pattern was the most prevalent with a frequency of
26 (76.46%) while the arch and whorl fingerprint
patterns were the least prevalent with a frequency of
4 (11.77%) each. For the right ring finger, the loop
fingerprint pattern was the most prevalent with a
frequency of 19 (55.88%) and the arch fingerprint
pattern was the least prevalent with a frequency of 1
(2.94%). The loop fingerprint pattern was the most
prevalent in the right little finger with a frequency of
29 (85.30%), while the arch was the least prevalent
with a frequency of 2 (5.88%).
Table 3b shows the frequency and
prevalence of the fingerprint pattern types on the left
hand of siblings. For the left thumb finger, the loop
fingerprint pattern was the most prevalent with a
frequency of 16 (47.06%), while the least prevalent
is the arch fingerprint pattern with a frequency of 6
(17.65%). For the left index finger, the whorl and
loop fingerprint patterns were the most prevalent
with a frequency of 12 (35.29%) each, while the arch
fingerprint pattern was the least prevalent with a
frequency of 10 (29.42%). The left middle finger had
the loop fingerprint pattern as the most prevalent
with a frequency of 23 (67.64%), while the arch
fingerprint pattern was the least prevalent with a
frequency of 5 (14.71%). For the left ring finger, the
loop fingerprint pattern was the most prevalent with
a frequency of 22 (64.71%), while the arch
fingerprint pattern was the least prevalent with a
frequency of 2 (5.88%). The loop fingerprint pattern
was the most prevalent in the left little finger with a
frequency of 27 (79.41 %), while the least prevalent
was the arch fingerprint pattern with a frequency of 2
(5.88%).
For each of the digits, the most predominant
of the fingerprint patterns was assessed (Tables 5a-
5b) to show the prevalence of the fingerprint patterns
on the ten digits. The whorl fingerprint pattern was
the most prevalent in the right thumb finger (Table
5a) with a frequency of 18 (45%) and the arch
fingerprint pattern was the least prevalent with a
frequency of 7 (17.5%). For the right index finger,
the loop fingerprint pattern was the most prevalent
with a frequency of 22 (55%), while the arch
fingerprint pattern was the least prevalent with a
frequency of 6 (15%). For the right middle finger, the
loop fingerprint pattern was the most prevalent with
a frequency of 28 (70%), while the arch and whorl
fingerprint patterns were the least prevalent with a
frequency of 6 (15%). For the right ring finger, the
loop fingerprint pattern was the most prevalent with
a frequency of 28 (70%), while the arch fingerprint
pattern was the least prevalent with a frequency of 2
(5%). The loop fingerprint pattern was the most
prevalent in the right little finger with a frequency of
34 (85%) and the arch fingerprint pattern was the
least prevalent with a frequency of 1 (2.5%).
For the left thumb finger (Table 5b), the
loop fingerprint pattern was the most prevalent with
a frequency of 19 (47.5%), while the arch fingerprint
pattern was the least prevalent with a frequency of 8
(20%). The loop fingerprint pattern was the most
prevalent in the left index finger with a frequency of
Iroanya et al. (2020); Fingerprints similarities between siblings
Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 60
19 (47.5%) and the arch fingerprint pattern was the
least prevalent with a frequency of 9 (22.5%). For the
left middle finger, the loop fingerprint pattern was
the most prevalent with a frequency of 27 (67.5%),
while the arch fingerprint pattern was the least
prevalent with a frequency of 5 (12.5%). The loop
fingerprint pattern was the most prevalent in the left
ring finger with a frequency of 23 (57.5%), while the
arch fingerprint pattern was the least prevalent with a
frequency of 2 (5%). For the left little finger, the
loop fingerprint pattern was the most prevalent with
a frequency of 34 (85%), while the arch fingerprint
pattern was the least prevalent with a frequency of 2
(5%).
Fingerprint Ridge Patterns
The ridge patterns were also analysed to access the
level of similarity between the siblings. The ridge
types accessed were whorl, central pocket loop
whorl, double loop whorl, accidental whorl, plain
arch, tented arch, radial loop and ulnar loop.
Table 6shows the frequency of the ridge pattern
distribution of the siblings. The ulnar loop fingerprint
pattern had the highest frequency of 194 (57.06%),
while the least was the accidental whorl fingerprint
pattern with a frequency of 6 (1.76%).
Table 7 shows the frequency of ridge
pattern distribution of the non-siblings. The result
revealed that the ulnar loop fingerprint pattern also
had the highest frequency of 243 (60.75%) and the
accidental fingerprint pattern also had the least
frequency of 0.
The prevalence of the fingerprint pattern
types was investigated in each of the ten digits of
each individual in the sampled population. In the
sampled population of siblings (Table 8a), the right
thumb finger had the whorl fingerprint as its most
prevalent fingerprint pattern type with a frequency of
55.88%, loop (52.94%) in the right index finger, loop
(76.46%) in the right middle finger, loop (55.88%) in
the right ring finger and loop (85.30%) in the right
little finger.
In the left thumb finger, the loop fingerprint
with a frequency of 47.06% was prevalent, loop and
whorl (35.29%) were prevalent in the left index
finger, loop (67.64%) in the left middle finger, loop
(64.71%) in the left ring finger and loop (79.41%) in
the left little finger.
In the sampled population of the non-
siblings (Table 8b), the right thumb finger had the
whorl fingerprint as its most prevalent fingerprint
pattern type with a frequency of (45%), loop (55%)
in the right index finger, loop (70%) in the right
middle finger, loop (70%) in the right ring finger and
loop (85%) in the right little finger.
In the left thumb finger, the loop fingerprint
with a frequency of (47.5%) was prevalent, loop
(47.5%) was prevalent in the left index finger, loop
(67.5%) in the left middle finger, loop (57.5%) in the
left ring finger and loop (85%) in the left little finger.
DISCUSSION
This study revealed that siblings have a higher
percentage similarity between their fingerprint
patterns than non-siblings. Fingerprint pattern types
are mostly genetically inherited, but the individual
details (the ridge patterns, minutiae, etcetera are
influenced by the position in the womb of the mother
and also the environmental conditions thereby
leading to the uniqueness of the fingerprint [15].
Humans possess the friction ridge skin (FRS) which
covers the surface of their hands and feet. The FRS is
unique and permanent - no two individuals
(including identical twins) have the exact FRS
arrangement, although as identical twins their
percentage similarity will be high and they might the
same fingerprint pattern types. The arrangement of
the ridges and features do not change throughout a
person’s lifetime, with the exception of significant
damages that create a permanent scar [16].
In this study, an investigation was carried
out to determine if siblings have a high percentage
similarity between their fingerprint pattern types.
Among the seventeen (17) sets of siblings sampled,
the average percentage similarity was 67.65%:
fourteen (14) showed a percentage similarity of 50%
and above while three (3) sets showed a percentage
similarity of 40% and below. This clearly suggests
that siblings have a high percentage similarity
between their fingerprint pattern types. The
frequency of the fingerprint pattern types in the
sampled population of both the siblings and non-
siblings revealed that loop was the most prevalent
fingerprint pattern type among the siblings and non-
siblings with frequencies of 193 (56.76%) and 250
(62.5%) respectively, while the arch was the least
prevalent with frequencies of 41 (12.06%) and 48
(12%) respectively. Most studies have shown ulnar
loop as having the highest percentage in normal
population followed by whorl, arch and radial loop
[17]. These findings agree with the findings of Singh
et al. [7] who reported that the loop fingerprint
pattern type was the most common fingerprint
pattern type which constitutes about 60-65% of the
human population and the least common fingerprint
pattern type is the arch which constitutes about 5% of
the human population. Hawthorne [18] reported that
65% of the fingerprints he analysed were loop
pattern, 30% were whorl pattern, and only 5% were
arch pattern. Sam et al. [19] also reported that loops
were the predominant pattern in both male and
female subjects who participated in the study,
followed by whorls in South Indian Population.
In fingerprints, there is a general flow of the
ridges that translates into one of the three major
pattern types: whorl, loop or arch. It is very possible
to have just one, two or all three pattern types on an
individual’s ten fingers. Therefore, an individual
cannot be identified based on pattern type alone but
also based on the ridge patterns known as the
Iroanya et al. (2020); Fingerprints similarities between siblings
Nigerian Journal of Scientific Research, 19 (1): 2020; January -February; njsr.abu.edu.ng; ISSN-0794-0319 61
minutiae which includes: core, island, dot, bridge et
cetera. In this study also, the distribution of the ridge
pattern type was determined. The ulnar loop had the
highest frequency in the sampled population of the
siblings and non-siblings with frequencies of 194
(57.06%) and 243 (60.75%). This corresponds with
the research carried out by Ekanem et al. [20] in
Nigeria who reported that the most prevalent ridge
pattern type among those who participated in his
study was the ulnar loop (44.9%). Abue et al. [21]
also documented that the dermatoglyphic pattern of
percentage frequency of the digits and palms of
Nigerians residing in Lagos, Nigeria were ulnar loop
(79.5 %), whorls (42.4 %), arch (12.4 %), and radial
loops (9.3 %), respectively.
Kucken and Newell [15] stated that the
exact arrangements of the ridges, minutiae and other
identifying features, however, are random and not
genetically linked and thus not inheritable. This
implies that an individual is more likely to share
pattern type with their family members than
unrelated individuals, but their Friction Ridge Skin
(FRS) will always be unique.
CONCLUSION
The result of this study showed that siblings have a
higher percentage similarity between their fingerprint
pattern types than non-siblings but their fingerprints
are still very unique due to individual fingerprint
details known as the minutiae and also because of
developmental timing and womb environment that
also influence the fingerprint minutiae. This study
therefore will help in investigating and resolving
civil and criminal cases such as family conflicts and
cases of murder, respectively.
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