A New Born Child Authentication System using Image Processing

International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169
Volume: 5 Issue: 8 244 – 248
_______________________________________________________________________________________________
244
IJRITCC | August 2017, Available @ http://www.ijritcc.org
_______________________________________________________________________________________
A New Born Child Authentication System using Image Processing
Mr.Akash Ulhas Nandurkar
M.Tech 2nd Year (Computer Sci. and Engg.)
D.R.G.I.T & Research
Prof. Zeeshan I. Khan
M.Tech (Computer Sci. and Engg.)
D.R.G.I.T & Research
Abstract: - The Missing, swapping, mixing, and illegal adoption of new born child is a global challenge and research done to solve this issue is
minimal and least reported in the literature. As per our knowledge, there is no biometric system currently available that can be effectively used
for new born child identification. The manual procedure of capturing inked footprints in practice for this purpose is limited for use inside
hospitals and is not an effective solution for identification purposes. Hence, a new born child personal authentication system is proposed for this
issue based on multi biometrics. The biometric traits considered are the footprint of the new born child and the fingerprint of the mother. An
appropriate fusion scheme is implemented to overcome the drawbacks of a single modality. The experimental results are promising and prove to
be an effective system.
Keywords:-Newbornt,Footprint , Fingerprintt, Biometric etc.
__________________________________________________*****_________________________________________________
1. INTRODUCTION
The newborn swapping and child abduction are
challenging issues. Traditional methods of identification of
such child have some drawbacks. Such as, method of practice
is to tie a number band around the hands/legs of the newborn
as a measure of identity. This number band is same as the one
which is also tied to the mother of the infant. At the time child
kidnapping or abduction, mixing of babies, multiple claims for
an infant in any hospitals, birthing centers causes emotional
breakdown and confusion. This raises a question on the
effectiveness of the such offline methods and the method of
tying number bands (ID bands). This eventually leads to the
DNA test at times. Hence, biometrics can be used to solve
such identity issues. In the online system, by a digital source
and computers are used for processing and storage. The
newborn’s footprint images captured using a high resolution
camera. The fingerprint of the newborn’s mother acquired by
a fingerprint scanner. wherein footprint of newborn and finger
print of their mother is used for recognition.
Biometric system is a pattern-recognition system
recognizes a person based on feature vector derived from a
specific biological characteristics such as Physiological
biometric identifiers include fingerprints, hand geometry, ear
patterns, eye patterns (iris and retina), facial features, and
other physical characteristics. Behavioral identifiers include
voice, signature, key stroke, and others. The Present method of
footprint, fingerprint acquisition in hospitals is inked footprint
of the newborn along with the fingerprint of the mother. This
is stored in a file which forms the medical database. This
method of image acquisition is offline. The image acquisition
done in the primary health centre. Further, implementation of
bimodal authentication in hardware as embedded system
enhances the overall performance of the system as a
standalone device. A complex IC that integrates the major
functional elements such as programmable processor, on-chip
memory, accelerating function hardware e.g.: GPU, both
hardware and software, analog components into a single chip
or chipset is called system on chip (SoC). Thus, reduce overall
system cost, increase performance, lower power consumption
and reduce size and draws low power.
2. LITERATURE REVIEW
Weicheng shen, Marc surette and Rajiv khanna works on
the problems in identity of an individual. The technology used
is automated biometric based identification. Method is
classifying automated biometrics-based systems into two major
categories: one-to-one systems and one-to-many systems. A
one-to-one system compares the biometric information
presented by an individual, these systems are designed to detect
the identity of an individual when it is unknown or it is
provided. One-to-many system compares the biometrics
information presented by an individual with all the biometric
information stored in a data base and decides whether a match
can be declared. These systems typically contain a series of
complex technologies that work together to provide the desired
result.[1]
Oscar Coltell, JosC M. Badia and Guillermo Torres comes
with the solution for problem that biometric authentication
system have low result regarding computational and economic
cost. Hence, suggested a first prototype of a software system
to elicitate sets of 20 password stroke samples, named attacks,
with a population of 10 different users totaling 200 attacks.
The results obtained demonstrate that users follow generally
certain patterns when they are writing their password, and are
possible to reinforce the user’s password authentication
method by means of the analysis of user stroking patterns.
This is very cost effective and need not require expensive
device. In addition to, it is necessary to increase the population
size and number of samples to establish standard and reliable

Volume: 5 Issue: 8 244 – 248
_______________________________________________________________________________________________
245
_______________________________________________________________________________________
rules. Finally, it is very difficult to find a general user pattern
applied to every password and when password are letters and
number without specific mean method is less effective.[2]
In this paper author implement a multimodal biometric
identification system based on the features of the human hand,
Because single physical behavior characteristics can fail in
identification. They describe a new biometric approach to
personal identification using Eigen finger and Eigen palm
features, with fusion applied at the matching-score level.
Figure1. Block diagram of implemented system

Volume: 5 Issue: 8 244 – 248
_______________________________________________________________________________________________
246
_______________________________________________________________________________________
The identification process can be divided into the
following phases: capturing the image, preprocessing,
extracting and normalizing the palm and strip-like finger sub
images, extracting the Eigen palm and Eigen finger features
based on the K-L transform, matching and fusion and finally, a
decision based on the (k, l)-NN classifier and thresholding.
The system achieve better result in terms of total error rate.
The time required for system is 0.565 sec [3]
The author recommended a system for reliable Tracking
and identification of children in intensive health care. A
widely suggested Bkiller application for the radio frequency
identification (RFID) technology. Safety for patients is
empowered by letting hospital staff know exactly the location
of every patient inside the hospital. This information is also
strongly connected to the correct identification of the patient,
which is the base for every patient-driven healthcare
management process.
Figure 2. Baby tag and Pilot area for system installation
A children’s resuscitation is an interesting case patients’
identity can easily be confused (in case of infants, they are still
not recognizable even in the eyes of their parents). They use
anti-collision algorithm also they have provided a planning
method to correctly identify the technical solution that best
responds to the design aims and constraints in a patients
tracking applications. The activation frequency is 2.45 GHz
and 433 MHz for communication but it is crucial that whole
staff to be trained.[4]
Natasa Glisovic found difficulty in paternity identification
because DNA test is costlier. Hence, proposed a system about
mutations can involve large sections of DNA becoming
duplicated, usually through genetic recombination.DNA
profiling and mutation technology used. Novel genes are
produced by several methods, commonly through the
duplication and mutation of an ancest ral gene, or by
recombining parts of different genes to form new
combinations with new functions. In the work, domains act as
modules, each with a particular and independent function, that
can be mixed together to produce genes encoding new proteins
with novel properties. This allows one gene in the pair to
acquire a new function while the other copy performs the
original function. Other types of mutation occasionally create
new genes from previously. Paternity can be determined pre-
natally, or before a baby is born, from CVS samples or
amniotic (fluid). Programming all done in C language and this
software supports all possible combination. Excluding relative
from paternity test result becomes difficult when mutation of
STR in consideration.[5]
In this paper author find problem in locating missing
people. Hence, suggest that face biometrics for helping with
the identification of missing children. The basic underlying
technologies involved in such situations are face recognition,
identity verification and age progression As part of the efforts
to deal with challenging aspects of face recognition a number
of researchers considered the problem of age progression and
age invariant face recognition (for a comprehensive review on
this topic see ). Also special cases of face recognition, such as
matching of sketches and mug shots to real images were
considered in an attempt to develop face-matching algorithms
that can be used for identity verification in law enforcement
applications also AAM, HOG Phog and FD algorithm used.
Figure 3. Distribution of real and synthetic sample
A real life scenario that involves identity verification of a
missing child and provide important clues for software
computation framework.[6]
S.Sivaranjani and S.Sumathi implemented a system for
newborn swapping in which, required images are acquired for
recognition consists of 6 samples of same newborn footprint
and corresponding 6 samples of their mothers fingerprint.
Then the collected samples undergoes 5 main steps namely (1)
Image Acquisition (2) Image enhancement (3) Binarization (4)
Thinning (5) Feature Extraction.

Volume: 5 Issue: 8 244 – 248
_______________________________________________________________________________________________
247
_______________________________________________________________________________________
Figure 4. Thinning of fingerprint
Figure 5. equalize image of footprint
The extracted features in the form of template are stored in
database. When the input image is given to their system it
undergoes all the pre-processing stage followed by pattern
matching stage finally and uses SIFT,GUO, Hall’s and
RANSAC algorithm. A decision is made based on match score
if the given input is authenticated or not. It is a low cost
solution for child swapping.[7]
Mr. Ashish R. Dandekar and Prof. M. S. Nimbarte
implemented system in which there are many social
networking web sites used by people and number of photos is
uploaded by them. But from photos it is difficult to predict the
relationship among the people if necessary. So there is need of
system for automatic identification and prediction of
relationship among them, specifically kinship from photo. So,
they implemented system, which uses Computer Vision, Face
recognition, Feature extraction and classification to solve this
problem. Implemented system first detects all the features
from given photo then extracts them from the faces using
Local binary Pattern.
Figure 6. Block diagram of verification
They observe in experiment that LBP features perform
stably and robustly over a useful range of less resolutions of
facial images. They implemented an algorithm to predict the
most likely kin relationships embedded in an image from three
input images of child, mother and father. Experimental results
have shown their system can effectively annotate the
verification of family relation. time required for system is
12.499sec.[8]
In this paper author investigates a novel method in order to
extract the optimal discriminant features from FKP images.
This method use the 1D-Log Gabor filter, the Gabor filter
bank and the Linear Discriminant Analysis (LDA). In the first
step, the Region of Interest (ROI) of a FKP images is analysis
with a 1D Log-Gabor wavelet to extract the preliminary
feature which is presented by the real parts of the filtered
image. In the second step, a Gabor filter bank is applied on the
preliminary feature in order to selection only the
discriminative features of FKP image. Finally, in the third
step, the LDA technique is used to reduce the dimensionality
of this feature and enhance its discriminatory power.
Figure 7. Block diagram of proposed system
Their biometric system is based on Nearest Neighbor
classifier which uses the cosine Mahalanobis distance for the
matching process. the method achieves higher accuracy but
single finger types yield not give better result compare to
multiple finger.[9]
3. CONCLUSION
To avoid the problems facing during matching of kids and
mother after the newborn swapping and child abduction
Biometric identification techniques is a great tool. While
discussing of all the available biometric authentication
systems, technique of matching of fingerprint and footprint of
mother and infant is very effective because it is low cost
solution to the newborn swapping. The use of various
algorithms such as SIFT, Fingerprint enhancing algorithm,
GUO, Hall’s algorithm and RANSAC & implementation on
raspberry pi enhances the overall performance to shoot out the
problem.
4. ACKNOWLEDGEMENT
I would like to thanks Prof. A. P. Bagade Assistant
Professor, Electronics and Telecommunication department,
B.D.C.E for his valuable suggestion. I would thank to my
college for providing valuable facilities which helps me in my
research work. I also express thanks to my parents, friends and
colleagues.
REFERENCES
[1] Weicheng shen, Marc surette and Rrajiv khanna,
“Evaluation of Automated Biometrics-Based Identification
and Verification Systems” proceedings of the ieee, vol. 85,
no. 9, september 1997.

Volume: 5 Issue: 8 244 – 248
_______________________________________________________________________________________________
248
_______________________________________________________________________________________
[2] Oscar Coltell, JosC M. Badia and Guillermo Torres
“Biometric Identification System Based in Keyboard
Filtering” IEEE1999.
[3] Slobodan Ribaric and Ivan Fratric “A Biometric
Identification System Based on Eigenpalm and Eigenfinger
Features” IEEE transactions on pattern analysis and
machine intelligence,nov 2005.
[4] Guido Biffi Gentili,Fabrizio Dori and Ernesto Iadanza.
“Dual-Frequency Active RFID Solution for Tracking
Patients in a Children’s Hospital. Design Method,Test
Procedure, Risk Analysis, and Technical Solution.”
Proceedings of the IEEE . 9, September 2010.
[5] Natasa Glisovic “Support system in deciding paternity test
which involves mutations” IEEE 10th Jubilee International
Symposium on Intelligent Systems and Informatics •
September 20-22, 2012, Subotica, Serbia.
[6] Andreas Lanitis and Nicolas Tsapatsoulis “lessons learned
from the application of biometric-tests on a real case
involving identity verification of a missing child”, 2014
IEEE.
[7] Sivaranjani, S.Sumathi. “A Review on Implementation of
Bimodal Newborn Authentication using Raspberry Pi”,
Proceedings of 2015 Global Conference on Communication
Technologies (GCCT 2015) 2015.
[8] Mr. Ashish R. Dandekar, Prof. M. S. Nimbarte
“Verificationof Family Relation from Parents and Child
Facial Images” IEEE 2015.
[9] Mourad chaa, Naceur-Eddine Boukezzoula, Abdallah
Meraoumia and Maarouf Korichi “An Efficient Biometric
Based Personal Authentication System Using Finger
Knuckle Prints Features” 2016 IEEE.

A New Born Child Authentication System using Image Processing

More Related Content

What's hot (20)

Similar to A New Born Child Authentication System using Image Processing (20)

More from rahulmonikasharma (20)

Recently uploaded (20)

A New Born Child Authentication System using Image Processing