Biometric Recognition(Biometrics) is a pattern-recognition system that identifies a person based on their physiological and behavioral traits.It helps to avoid baby swapping,identity theft,identity fraud and illegal adoptions in hospitals.

1. Biometric Recognition of Infants using Fingerprint,
Iris, and Ear Biometrics
PRESENTED BY: TRESA MARIA JACOB
COLLEGE OF ENGINEERING,CHENGANNUR
November 30, 2022
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 1 / 26

2. CONTENTS
1 INTRODUCTION
2 RELATED WORKS
3 PROBLEM DEFINITION
4 PROPOSED SYSTEM
5 ARCHITECTURE
6 EVALUATION
7 CONCLUSION
8 FUTURE WORKS
9 REFERENCES
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 2 / 26

3. INTRODUCTION
▶ Globally over 1 billion people lack legal identification and almost half of
them are infants and children.
▶ Recognition of newborn after birth is a critical issue for hospitals,
maternity ward and other places where multiple birthstake place.
▶ Challenge:
Existing Technology is not capable of acquiring biometric information
from newborn infants due to imaging devices and uncooperative nature
of infants.
▶ To solve this challenge,a prototype biometric recognition system is
developed to acquire biometric data from young children.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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4. INTRODUCTION...
Figure: Analysis of various modalities from birth to adulthood.
▶ Several biometric modalities like voice recognition,face recognition,finger
and palm-based methods...etc are considered.
▶ Finally decided to focus on fingerprint,iris and outer ear shape based on:
universality,uniqueness permanence, collectability,performance,
acceptability and resistance to circumvention.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 4 / 26

5. RELATED WORKS
S.NO Paper Methodology Limitation
1
Multimodal biometric
recognition for toddlers
and pre-school children.
P. Basak, S. De, M.
Agarwal, A. Malhotra, M.
Vatsa, and R. Singh,Oct
2017
1. Face, fingerprint, and iris
modalities of over 100 children
(age range of 18 months to
4 years) are captured in two
different sessions.
2. Demonstrates that iris
biometric modality can provide
the highest genuine accept rate,
particularly when both left and
right irises are combined.
Data collection from young
children requires special
care and patience.
2
Newborn’s ear recognition:
Can it be done?
S. Tiwari, A. Singh,
and S. K. Singh,Nov.2011
1. Preparation of newborn ear
database from 210 individuals.
2. Ear images were captured by
first acquiring side face images.
Accuracy is low.
Average total delay of the
operation is high.
3
Newborn’s biometric
identification: Can it be
done?
D. Weingaertner, O.
Regina, P. Bellon, and L.
Silva,2011
1. Conducted survey based
on dactyloscopic impressions
and then present a newly
developed digital sensing
equipment capable of
providing high definition
images of the baby’s palms and
soles.
2. Images were collected
moments after the birth.
Lack of large public
database of ear acquired
under real working
conditions.
Accuracy is low.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 5 / 26

6. PROBLEM DEFINITON
▶ Most of the biometric systems developed are for adults and very few of
them address the issue of newborn identification.
▶ Existing technologies are not capable of acquiring biometric information
from infants and matching it to the same individual during growth with
accuracy and reliability.
▶ The level of security is a very crucial issue in the maternity ward,missing
and swapping of newborn,identity theft and identity fraud.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 6 / 26

7. PROPOSED SYSTEM
In this system, 3 frameworks are proposed for:
1 IRIS ACQUISITION
2 EAR ACQUISITION
3 FINGERPRINT ACQUISITION
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 7 / 26

8. ARCHITECTURE OF IRIS ACQUISITION
Figure: Iris Image Acquisition:
Go to slide 11
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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9. ARCHITECTURE OF EAR SEGMENTATION
Figure: Ear Segmentation Process
Go to slide 12
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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10. ARCHITECTURE OF FINGERPRINT PROCESSING
Figure: Steps required to process and compare the contactless fingerprints.
Go to slide 13
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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11. METHODOLOGY
A. IRIS
1) ACQUISITION METHODOLOGY
▶ Iritech IriShield BK 2121U Scanner-II is used to collect the images.
▶ Collect three images of both eyes of each child.
2) DATA ANALYSIS METHODOLOGY
▶ Discard low-quality images from database.
▶ Apply Daugman’s iris recognition.
Figure: Iris Image Segmentation Process
Back to slide 9
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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12. METHODOLOGY...
B. EAR
1) ACQUISITION METHODOLOGY
▶ Acquisition of 2D ear images are performed by collecting photographs of
both left and right ear images from children.
▶ A 1080p LogiTech webcam is used,which provides 2MP images.
2) DATA ANALYSIS METHODOLOGY
▶ Images are pre-processed to reduce the effect of noise and illumination.
▶ Then,the region of the ear is detected.
Figure: Representation of a) original image b) detected skin region c) detected edges d) detected ear
region, and e) detected edges.
Back to slide 10
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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13. METHODOLOGY...
C. FINGERPRINT
1) ACQUISITION METHODOLOGY
▶ Fingerprints were acquired by contactless infant fingerprint acquisition
device,achieves a resolution of 2500dpi and is converted into a greyscale
image.
STEPS:
▶ Background Removal: Based on color-based background
segmentation,fingertip is isolated from its background.
▶ Scale correction: Images are scaled to a similar number of inter-ridge
pixels than fingerprints from adults captured at 500dpi.
▶ Enhancement: Extract fingerprint patterns by techniques like contrast and
illumination correction,noise filtering and sharpening.
▶ Quality Estimation: National Institute of Standards and Technology’s
Fingerprint Image Quality(NFIQ) scoring method is used. All images with
quality levels of 1-3 are accepted while others are regarded as low quality
and failure to acquire.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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14. METHODOLOGY...
2) DATA ANALYSIS METHODOLOGY
▶ Determine image quality under different scenarios.
STEPS:
▶ Collect three impressions from each finger.
▶ Automated conversion of fingerprint images into a format which is
compatible with commercial off-the-shelf fingerprint processing software.
▶ Perform the quality assessment.
▶ Perform the verification simulation.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 14 / 26

15. EVALUATION
A. DATA COLLECTION
▶ Data was collected from volunteer participants at a public clinic.
▶ Participants were split into 3 groups,based on vaccination schedules.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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16. EVALUATION...
B. IRIS
1) DATASET
▶ Iris images from 56 participants under the age of 1 year are collected.
▶ From each participant,3 impressions from each eye are taken.
▶ Due to inability of infants to follow the instructions,less than 3
impressions were taken in some cases.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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17. EVALUATION...
2) DATA CLEANING AND QUALITY ANALYSIS
▶ Data cleaning is performed by removing all images in which iris is not
clearly visible.
▶ Only 144 of the possible 354 images are usable.
▶ Also,images that were acquired with visible irises may not be of good
quality.
3) PERFORMANCE ANALYSIS
▶ Performance of collected data is measured by EER(Equal Error Rate).
▶ EER is a biometric security system algorithm used to predetermine the
threshold values for its false acceptance rate and its false rejection rate.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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18. EVALUATION...
C. EAR
1) DATASET
▶ Ear images are acquired using Logitech HD 1080p WebCam camera.
▶ Collected images from 71 participants,from the age of 6 weeks and above.
▶ Six ear images are captured with three of the left and three of the right
ear.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 18 / 26

19. EVALUATION...
2) DATA CLEANING AND QUALITY ANALYSIS
▶ High acquisition rate compared to iris and fingerprint modality for
infants.
▶ Due to pose variation and low image quality,only useful images were
collected.
3) PERFORMANCE ANALYSIS
▶ Histograms of Oriented Gradients(HOG) features are extracted from two
ear images and compared based on Hamming distance method.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 19 / 26

20. EVALUATION...
D. FINGERPRINT
1) DATASET
▶ Collected fingerprints from 66 participants under the age of 1 year.
▶ From each child, 3 impressions from 6 fingers were taken.
▶ For comparison, fingerprints were also acquired using standard 500dpi
fingerprint scanner,the Futronic FS-88.
Figure: Representation of (a) the acquisition image of an infant’s fingerprint
(b) image processing to convert the fingerprint into a format (c) minutiae
extraction
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 20 / 26

21. EVALUATION...
2) DATA CLEANING AND QUALITY ANALYSIS
▶ Determine image quality using NFIQ score.
▶ The scores range from 1 to 5,with 1 being the best quality and 5 being the
worst.
3) PERFORMANCE ANALYSIS
▶ Performance of collected data is measured by EER.
▶ The lower the equal error rate value, higher the accuracy of the biometric
system.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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22. DEMONSTRATION
▶ A Biometric Recognition system is developed for infants by using
Fingerprint, Iris and Ear Biometrics.This system protect children from
exploitation in various ways such as identity theft,identity fraud..etc
Demo Video
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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23. CONCLUSION
▶ Developed biometric systems for recognising infants by their
fingerprints,irises and outer ear shape.
▶ Ear biometrics is easy to acquire from infants and the existing
technologies developed for adult ears do works for infants also.
▶ Iris biometrics can be used to successfully match individuals from as
early as 6 weeks and that acquisition rate improves during growth.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
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24. FUTURE WORKS
▶ Combine these biometric modalities to create more robust and accurate
biometric recognition systems.
▶ Extend these systems for effective use from birth to adulthood.
▶ Improvements on the fingerprint acquisition were made to create a
strong,flexible and robust system.
COLLEGE OF ENGINEERING,CHENGANNUR Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics
November 30, 2022 24 / 26

25. REFERENCES
[1] Y. Moolla, A. De Kock, G. Mabuza-Hocquet, C. S. Ntshangase, N. Nelu-
fule and P. Khanyile, ”Biometric Recognition of Infants using Fingerprint, Iris,
and Ear Biometrics,” in IEEE Access, vol. 9, pp. 38269-38286, 2021.
[2] S. Adel Bargal, A. Welles, C. R. Chan, S. Howes, S. Sclaroff, E. Ragan, C.
Johnson, and C. Gill, “Image-based ear biometric smartphone app for patient
identification in field settings,” in Proc. 10th Int. Conf. Comput. Vis. Theory
Appl., 2015, pp. 171–179.
[3] C. S. Ntshangase and D. Mathekga, “The comparison of ear recogni-
tion methods under different illumination effects and geometrical changes,” in
Proc. Int. Conf. Adv. Big Data, Comput. Data Commun. Syst. (icABCD), Aug.
2019, pp. 1-6.
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