The document discusses several biometric methods including palm print recognition, ear biometrics, and DNA biometrics. For palm print recognition, it describes how palm prints contain unique ridge characteristics similar to fingerprints and can be used for identification. It outlines the palm print recognition process including acquisition, preprocessing, feature extraction, matching, and database storage. For ear biometrics, it discusses different identification methods using ear photos, earmarks, and thermograms. DNA biometrics is described as using genetic analysis to identify individuals from biological samples and its use in forensic science, medical diagnosis, and establishing ancestry.
Review of Detection & Recognition Techniques for 2D Ear Biometrics Systemshritosh kumar
Abstract
Authentication of a person's identity is a very old but challenging problem.
There are three common ways which are used for authentication. First one
is based on what a person has (Possession) such as keys, identity cards etc.
Second mode of authentication is based on what a person knows or
remembers (Knowledge) such as passwords, PINs etc. Third way of
authentication is based on what a person carries, i.e. the characteristics of
a human being (Biometrics). Biometrics is the science of establishing
human identity by using physical or behavioural traits such as face,
fingerprints, palm prints, iris, hand geometry, ear, and voice. There are
some significant works which have been carried out in past few years in
the field of ear biometrics. In this survey discusses various technique of ear
Detection & Recognition for 2D ear biometric, and provides good future
prospects for the upcoming researchers in the field of ear biometric.
This paper presents an efficient ear recognition technique which derives benefits from the local features of the
ear and attempt to handle the problems due to pose, poor contrast, change in illumination and lack of
registration. Recognizing humans by their ear have recently received significant attention in the field of
research. Ear is the rich in characteristics. This paper provides a detailed survey of research done in ear
detection and recognition. This survey paper is very useful in the current state-of- art for those who are working
in this area and also for those who might exploit this new approach.
In this presentation, we have covered all the key aspects of biometrics like what is biometrics, different concepts related to biometrics, different biometrics technology like working of fingerprint scanning, facial recognition, hand geometry, iris scanning, etc. the presentation mainly focuses on the biometric and what biometric term actually means
Review of Detection & Recognition Techniques for 2D Ear Biometrics Systemshritosh kumar
Abstract
Authentication of a person's identity is a very old but challenging problem.
There are three common ways which are used for authentication. First one
is based on what a person has (Possession) such as keys, identity cards etc.
Second mode of authentication is based on what a person knows or
remembers (Knowledge) such as passwords, PINs etc. Third way of
authentication is based on what a person carries, i.e. the characteristics of
a human being (Biometrics). Biometrics is the science of establishing
human identity by using physical or behavioural traits such as face,
fingerprints, palm prints, iris, hand geometry, ear, and voice. There are
some significant works which have been carried out in past few years in
the field of ear biometrics. In this survey discusses various technique of ear
Detection & Recognition for 2D ear biometric, and provides good future
prospects for the upcoming researchers in the field of ear biometric.
This paper presents an efficient ear recognition technique which derives benefits from the local features of the
ear and attempt to handle the problems due to pose, poor contrast, change in illumination and lack of
registration. Recognizing humans by their ear have recently received significant attention in the field of
research. Ear is the rich in characteristics. This paper provides a detailed survey of research done in ear
detection and recognition. This survey paper is very useful in the current state-of- art for those who are working
in this area and also for those who might exploit this new approach.
In this presentation, we have covered all the key aspects of biometrics like what is biometrics, different concepts related to biometrics, different biometrics technology like working of fingerprint scanning, facial recognition, hand geometry, iris scanning, etc. the presentation mainly focuses on the biometric and what biometric term actually means
Biometrics is the technical term for body measurements and calculations. It refers to metrics related to human characteristics. Biometrics authentication (or realistic authentication) is used in computer science as a form of identification and access control.
PPT On Biometrics Technology for Engineering student. It contains all the basic of Biometrics. Contents are taken from different sources. I Presented it in 5th semester of B.tech. It is a nice project for engineering students. from Fingerprint to the vein scanning process and voice recognization pattern are explained in a short way.
Applications of Biometrics in Technologyiamsanjayk
Biometric in the field of Computer science ! This is a powerpoint presentation prepared as a first year participation in college presentation competition. Topic - Applications of biometrics in technology. This was my first attempt. Hope it comes in use for people in need of a simple presentation.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Biometrics is the technical term for body measurements and calculations. It refers to metrics related to human characteristics. Biometrics authentication (or realistic authentication) is used in computer science as a form of identification and access control.
PPT On Biometrics Technology for Engineering student. It contains all the basic of Biometrics. Contents are taken from different sources. I Presented it in 5th semester of B.tech. It is a nice project for engineering students. from Fingerprint to the vein scanning process and voice recognization pattern are explained in a short way.
Applications of Biometrics in Technologyiamsanjayk
Biometric in the field of Computer science ! This is a powerpoint presentation prepared as a first year participation in college presentation competition. Topic - Applications of biometrics in technology. This was my first attempt. Hope it comes in use for people in need of a simple presentation.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Technology that identifies you based on your physical or behavioral traits- for added security to confirm that you are who you claim to be.(this ppt is very dear to me as i have given a talk on this topic twice. this also fetched me and migmar first prize at deen dayal upadhyay college- converging vectors - an inter college presentation competition organized by arya bhata science forum)
This paper explores biometrics and electronic voting in a bid to design a Biometrics-based E-Voting System that could be applicable in Ghana and other similar developing countries, its shortcomings and the advantages of the biometrics authentication module incorporated in the system.
This is a Fingerprint based class attendance system in higher institutions, The implementation take attendance of student in a class and give output of student eligibility status at the end of the semester or term
Performance of Gabor Mean Feature Extraction Techniques for Ear Biometrics Re...shritosh kumar
Abstract
Ear biometric recognition is used in a lot of applications as person identification in
criminal cases, investigation, and security purpose. Feature optimization stage
has an important role for accuracy of correct recognition. Gabor filter have a
problem of high dimension and high redundancy. Sampling filter is a problem of
not reducing features optimum way. In the proposed Gabor feature extraction
technique the Gabor features are filtered using proposed mean filter and obtained
optimum features for ear biometric dataset.
Biometrics Iris Scanning: A Literature ReviewOlivia Moran
The interest in Biometrics from both governments and industry has lead to the emergence of multiple Biometric technologies all with their own strengths and flaws. One currently at the forefront of Biometrics is iris scanning.
The process involved in the identification and verification of people using iris scanning is examined in this paper. The advantages and disadvantages associated with the utilisation of such a technology are also explored. A number of legal and ethical issues are highlighted. Iris scanning is looked at in comparison to other forms of Biometric technologies. Future work in the area of Biometrics is also considered in light of current developments.
Physical biometrics alludes to physiological elements on the human body that can fill in as ID, for example, a finger impression or retina filter. Organizations frequently gather and store physical biometric information to confirm personalities for a wide range of occupations, security being the clearest. Physical biometric distinguishing proof can likewise have other use situations where facial acknowledgment is utilized to recognize hot shots in a gambling club to further develop their client experience.
Implementation of Ear Biometrics as Emerging Technology in Human Identification System ...............1
B. Srinivasan and V. K. Narendira Kumar
Determining the Security Enhancement of Biometrics in Internet Passport Scheme using Cryptographic
Algorithms ........................................................................................................................................1
B. Srinivasan and V. K. Narendira Kumar
Novel Image Fusion Techniques using DCT .........................................................................................1
V. P. S. Naidu
High Performance Data mining by Genetic Neural Network ................................................................1
Dadmehr Rahbari
Parallel Ensemble Techniques for Data Mining Application .................................................................1
M. Govindarajan
A Hybrid Cryptosystem for Image using Chaotic Mapping ...................................................................1
Nidhi Sethi and Sandip Vijay
Investigating Factors Affecting Adoption and Implementation of m-Government in the South African
Department of Home Affairs: An on-going Research ..........................................................................1
Maleshoane Sepeame and Emmanuel Babatunde Ajala
Prospects of Thermal Management Techniques in Microprocessor Architecture .................................1
Ajaegbu Chigozirim, Shodiya A.S and Kuyoro Shade O.
Capacity Based Clustering Model for Dense Wireless Sensor Networks ...............................................1
S. R. Boselin Prabhu and S. Sophia
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Adopting level set theory based algorithms to segment human earIJCI JOURNAL
Human identification has always been a topic that interested researchers around the world. Biometric methods are found to be more effective and much easier for the users than the traditional identification methods like keys, smart cards and passwords. Unlike with the traditional methods, with biometric methods the data acquisition is most of the times passive, which means the users do not take active part in data acquisition. Data acquisition can be performed using cameras, scanners or sensors. Human physiological biometrics such as face, eye and ear are good candidates for uniquely identifying an individual. However, human ear scores over face and eye because of certain advantages it has over face. The most challenging phase in human identification based on ear biometric is the segmentation of the ear image from the captured image which may contain many unwanted details. In this work, PDE based image processing techniques are used to segment out the ear image. Level Set Theory based image processing is employed to obtain the contour of the ear image. A few Level set algorithms are compared for their efficiency in segmenting test ear images
Protection of Patient Identity and Privacy Using Vascular BiometricsCSCJournals
Biometric systems are being used in hospitals to streamline patient registration and identification, as an effective measure to protect patient privacy and prevent identity theft. Many Hospitals and Healthcare institutions are turning towards Vascular Biometrics which complement the biometric recognition with hygiene and improved accuracy. In this paper, a multimodal hand vein system and a multibiometric fingerprint-hand vein biometric system are proposed. The multimodal hand vein system is a non-invasive, contactless and fast system, which uses two different feature sets extracted from each hand vein image. The multibiometric system captures both the fingerprint as well as the hand vein of the patient and hence offers even more improved performance though the speed and the cost of the system as well as the hygiene are reduced. We have used the Euclidean classifier to calculate the performance rates namely the False Rejection Rate (FRR) and False Acceptance Rate (FAR) of the Vein System and the Fingerprint-Vein System. We have performed this analysis using a volunteer crew of 74 persons. The FRR and FAR were 0.46% and 0.7% in the former case and 0% and 0.01% in the latter case respectively. The multimodal or the multibiometric system could be used based of the Hospital‘s requirements.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Biometrics system
1. BIOMETRICS SYSTEM
ASSIGNMENT
Topic:
Methods of Palm print, Ear Biometrics and DNA.
Submitted by
Name:B.Keerthana
Reg No: 11MSE0251
Slot: C2
Faculty: Srinivasa Permual
PALMPRINT RECOGNITION
2. Palm print recognition inherently implements many of the same matching
characteristics that have allowed fingerprint recognition to be one of the most
well-known and best publicized biometrics. Both palm and finger biometrics are
represented by the information presented in a friction ridge impression. This
information combines ridge flow, ridge characteristics, and ridge structure of the
raised portion of the epidermis. The data represented by these friction ridge
impressions allows a determination that corresponding areas of friction ridge
impressions either originated from the same source or could not have been made
by the same source. Because fingerprints and palms have both uniqueness and
permanence, they have been used for more than a century as a trusted form of
identification. However, palm recognition has been slower in becoming
automated due to some restraints in computing capabilities and live-scan
technologies.
The five modules are described below:
(1) Palm print Acquisition:
A palm print image is captured by our palm print scanner and then the
AC signal is converted into a digital signal, which is transmitted to a computer for
further processing.
(2) Pre-processing:
A coordinate system is set up on basis of the boundaries of fingers so as to
extract a central part of a palm print for feature extraction.
(3) Textured Feature Extraction:
We apply a 2-D Gabor filter to extract textural information from the central
part.
(4) Matching:
A distance measure is used to measure the similarity of two palm prints.
(5) Database:
It is used to store the templates obtained from the enrolment phase.
Proposed Algorithm:
3. The block diagram of our method is shown in figure 1. As shown, the proposed
methods include three stages: palm detection, feature extraction and template
matching. When the system is in enrolment phase, the extracted features of palm
(ROI) are stored in system database. When the system is in test phase, extracted
template of new image is matched with stored templates in system databases.
Our proposed method is simple and significant algorithm that is invariant to
rotation, translation and scale variation.
Original image
Contourextraction
Palm detection
Database
ROI extraction
Edge detection by
Sobel operator
Radon
transform
Autocorrelation
method
Palm detection:
In some biometric systems based on palm print features a few pegs are used
to positioning the user hand. We removed pegs due to increase user acceptance
and just required from user to separating fingers while acquiring image. In this
stage, fingers extremities are used to identify the palm ROI. First, the hand
contour is extracted and distance between contour points and gravity point are
obtained.
Then locally extremes are labelled as peak and valley point. Using these
labelled points we could obtained the end points of index and small fingers. In
fact, this line is passes through these two points (p1 and p2). Finally, the square
region is detected as palm ROI.
Feature extraction:
M
a
t
c
h
i
n
g
4. In this step a feature vector is extracted from palm ROI that is include two substeps. (a) Projection of edged palm ROI, (b): autocorrelation method. As this
paper is based on radon transform and autocorrelation method, first we review
briefly these two methods. Note that the edge of image is found by Soble operator.
(a): signature contour.
(b): palm ROI .
Advantages of Palm print Biometrics:
Since the palm area is much larger, hence more distinctive features can be
captured compared to fingerprints. This makes it more even more suitable
in identification systems than fingerprints.
Disadvantages of Palm print Biometrics:
The palm print scanners are usually bulkier and expensive since they need
to capture a larger area than the fingerprints scanners.
5. Ear biometrics
Biometrics are unique physical or behavioral characteristics of an individual
which can be measured and thus compared to accurately verify or identify an
individual.
Universal: each person should possess the characteristics.
Unique: no two persons should share the characteristics.
Permanent: the characteristics should not change.
Collectable: easily presentable to a sensor and quantifiable.
6. EAR BIOMETRICS METHODS:
There are at least three methods for ear identification:
(i) Taking a photo of an ear,
(ii) Taking “earmarks” by pushing ear against a flat glass and
(iii) Taking thermo gram pictures of the ear.
Photo comparison:
Alfred Iannarelli has made two large-scale ear identification studies in 1989. In
the first study there were over 10,000 ears drawn from a randomly selected sample
in California. The second study was for researching identical and non-identical
twins. These cases support the hypothesis about ear uniqueness. Even the
identical twins had similar, but not identical, ear physiological features.
Alfred Iannarelli had been working 30 years as deputy sheriff in Alameda County,
California, as the chief of the campus police at California State University at
Hayward and in several other law enforcement positions. He became interested in
ears in 1948 and over the next 14 years classified about 7,000 ear’s from
photographs. The first version of the book describing his classification method
was published 1964. The second edition was published in 1989. Iannarelli does not
have academic background for his studies. (Morgan, 1999).
7. Earmarks:
Ear identification can be done from photographs or from video. There is another
possibility: the ear can be pressed against some material, e.g. glass, and the
‘earmark’ can be used as a biometric. This has been used in crime solving. In
England four delinquents have been judged between 1996-1998 by using only the
earmarks (Bamber, 2001). However In the Netherlands the court decided that the
earmarks are not reliable enough for judging (Forensic-Evidence News, 2000). The
Dutch found out that the earmarks usually doesn’t have enough details for
reliable identification. Also when there are no dependable proofs that ears are
unique, it was decided that ear identification cannot be used as evidence.
Thermo gram pictures:
In case the ear is partially occluded by hair the hair can be masked out of the
image by using thermo gram pictures (see figure 3). In the thermo gram pictures
different colours and textures are used to find different parts of ear. In the figure 3
the subject’s hair is between 27.2 and 29.7 degrees Celsius while the outer ear
areas range from 30.0 to 37.2 degrees Celsius. The ear is quite easy to detect and
localizable using Thermo gram imagery by searching high temperature areas.
(Burge et al., 2000).
Advantages – disadvantages:
Ears are smaller than e.g. faces reduced spatial resolution
Ears are not as variable as e.g. faces
We have almost none adjectives to describe ears: we can recognize people
from faces but can we recognize them from ears?
8. Deoxyribonucleic acid (DNA) Biometrics
Doctors now use genetic tests to detect specific types of inherited disease such as
Huntington's disease or cystic fibrosis. Tests have also been developed to identify
an inherited predisposition to certain types of breast cancer and Alzheimer's
disease. As more is learned about the information stored in DNA, DNA tests may
be used more widely in preventative medicine to help individuals avoid specific
foods or certain environmental conditions. DNA analysis is no longer confined to
genetic and medical research. Forensic science relies heavily on the ability of DNA
to identify the source of biological substances and determine who is most likely to
have committed a crime. This ability to identify an individual is enhanced by the
variety of substances that contain DNA, including blood, semen, saliva, hair,
urine, bone, teeth, feces, and tissues. Using saliva, the FBI were able to match
DNA samples from letters mailed to relatives by Theodore Kaczynski with DNA
obtained from stamps on letters mailed by the Unabomber.
Identification of specimens using DNA has had other benefits, in one
third of the cases where this technique has been used, DNA analysis has been able
to exonerate people wrongly accused of crimes. Prisoners wrongly accused of rape
or murders have been freed on basis of DNA evidence. DNA analysis is now a
common tool for establishing paternity, and it has been called on to identify
remains after tragedies such as airline accidents and the inferno at the Branch
Davidian complex in Waco, Texas. Anthropologists are using DNA analysis to
study the migration of human beings across the oceans and historians employ
these techniques to identify genetic disease in famous individuals. The variation
of DNA sequences between species and individuals has also been useful for
wildlife biologists attempting to track endangered species.
9. DNA structure:
The prime features of the structure which can be seen here are:
– two strands of DNA wrap around each other
– it is a right-handed helix
– there is a 2-fold axis of symmetry
– The two strands are colored differently to show that two
complementary molecules make up the duplex.
Is DNA a Biometric?
First of all, DNA differs from standard biometrics in several ways:
DNA requires a tangible physical sample as opposed to an impression,
image, or recording.
DNA matching is not done in real-time, and currently not all stages of
comparison are automated.
DNA matching does not employ templates or feature extraction, but
rather represents the comparison of actual samples.
Regardless of these basic differences, DNA is a type of biometric inasmuch as it is
the use of a physiological characteristic to verify or determine identity. DNA
testing is a technology with a high degree of accuracy however, the possibility of
sampling contamination and degradation will pose an impact on the accuracy of
the method.
Advances of DNA Biometrics:
The analysis of DNA took weeks and even months to process. With steady and
resilient research, developers have been able to reduce the entire process down to
less than 30 minutes. Organizations such as NEC have developed the world’s first
portable human DNA analyzer. This unit integrates all steps of the DNA analysis
process and is able to do so in approximately 25 minutes (Tech News). Although
this is completely unsuitable for access to a secure facility and is unacceptable to
use in a Security Network environment, advances are being made to expedite the
analysis process. While biometric standards, privacy issues, financial
expectations, accuracy and various other topics are in question, developers
continue to work closely with the NSTC and other technological organizations to
investigate and improve the DNA biometric process.