A review of biometric
technology along with
trends and prospects
J.A.Unar, Woo Chaw Seng, Almas Abbasi
Adviser:Frank. Yeong-Sung Lin
Present by Limin Zheng
Agenda
Introduction
Biometric systems
Biometric modalities
Multi-modal biometrics
Biometrics prospects
Conclusion
Introdution
Introdution
The ever increasing criminal and terrorist acts in public places,
government/private properties resulted in chaotic scenarios
thereby making the existing surveillance systems questionable –
“How effective is the surveillance system to prevent unlawful activities?”
“Does the system guarantee the required level of security?”
“Does the system distinguish an unauthorized user from an impostor reliably?”
“Is the system user friendly?”.
Introdution
In early stages, the identity manage- ment systems relied on cryptographic
methods requiring the users to remember a secret text (password) or keep
something with them (token, card) or a combination of both to prove their
identity.
Access control, computer logins, e-mail checking, making bank transactions,
border control, welfare disbursements etc.
However, the users challenged the efficacy of such systems.
Introdution
As an answer, the research community proposed the idea of human
identification based on physiological or behavioral attributes of
individuals very often termed as “Biometrics”.
Although biometrics is not the perfect solution but it offers several advantages
over knowledge and possession based approaches in the way that
1) there is no need to remember anything,
2) biometric attributes can not be lost, transferred or stolen,
3) offer better security due to fact that these attributes are very difficult to forge
and require the presence of genuine user while granting access to particular
resources.
Introdution
Any physiological or behavioral attribute can qualify for being a
biometric trait unless it satisfies the criteria such as
1) Universality
5) Performance
2) Distinctiveness
6) Acceptability
3) Invariance
7) Circumvention
4) Collectability
Introdution
1) The paper provides details about each biometric modality along
with prominent recognition techniques and public data sets
available to the researchers.
2) The article contains a rough quantitative analysis of individual
techniques in terms of accuracy.
3) The paper discusses multi-modal biometrics in detail which has
not been well covered in other review articles on the subject.
4) The paper contains current market statistics along with future
prospects for biometric based identification and authentication.
Biometric systems
Biometric systems
A biometric system is a pattern recognition system which matches the
salient or discriminatory features of acquired image (probe image)
with the features of pre-stored images (gallery image).
For doing so, every biometric system comprises of
1) Image acquisition module
2) Feature extraction module
3) Matcher module
4) Database module
Biometric systems
2.1. Modes of operation
2.1.1.Verification (positive recognition)
The user after submitting the biometric signature to the system
claims a parti- cular identity through a PIN, login name, etc.
Recognition system validates or voids user's claim by making a 1:1
(one-to-one) comparison between the submitted biometric signa- ture
and enrolled biometric signature associated with that parti- cular
identity.
Biometric systems
2.1. Modes of operation
2.1.2.Identification (negative recognition)
Recognition system tries to recognize the user by comparing the
submitted biometric signature to all the enrolled signatures in the
database by making 1:N (one-to-many) comparisons without specific
identity claim from the user.
Biometric systems
2.1. Modes of operation
2.1.3. Screening
This is an extension to identification where the biometric system
assures that a particular individual does not belong to a watch list of
identities by performing 1:N (one-to-many) comparisons throughout the
database.
Biometric systems
2.1. Modes of operation
Modes
Verification
Application
Computer logins, ATMs, e-commerce, access control and
user authentication on mobile devices [2].
Identification Issuance of ID cards, passports, riving licenses, border
crossing and welfare disbursements [1,2].
Screening
Airport security, surveillance activities, public place and
public events security etc. [4]
Biometric systems
2.2. Performance measurements
The performance or accuracy of a biometric system is data
dependent usually influenced by environmental and
performance factors.
Environmental Factors:
Temperature, humidity and illumination conditions
Performance Factors:
Capturing good quality images, composition of target user population, time interval
between the enrollment and verification phases and robustness of recognition
algorithms [2].
Biometric systems
2.2. Performance measurements
2.2.1. Sample acquisition errors
Environmental conditions surrounding the system give rise to
acquisition errors.
1) Failure to enroll error
2) Failure to capture error
Biometric systems
2.2. Performance measurements
2.2.2. Performance errors
These errors are used to measure the accuracy of biometric systems
in real environment. A brief description is given below:
1) False match rate (FMR) or false accept rate (FAR)
2) Falsenon – match rate(FNMR)orfalserejectrate(FRR)
3) Equal error rate (EER)
Biometric modalities
Biometric modalities
3.1. Hand region modalities
1) Fingerprints(BEST)
2) Palmprint
3) Hand geometry
4) Finger knuckle print
5) Finger nail bed
6) Hand vein pattern
Biometric modalities
3.1. Hand region modalities
Biometric modalities
3.1. Hand region modalities
Image acquisition methods:
1) Optical
2) Thermal
3) Silicon
4) Ultrasonic imaging
Exceptions:
1) Hand geometry → use a camera to acquire 3D image
2) Hand vein → beneath the skin thereby exposing hand to near infrared light
Biometric modalities
3.1. Hand region modalities
Advantage:
1) low cost imaging sensors
2) small template size
Disadvantage:
1) artificial gummy fingers → Recent trend : vein technology
Biometric modalities
3.2. Facial region modalities
1) Face
2) Ear shape
3) Teeth
4) Tongue print
Biometric modalities
3.2. Facial region modalities
Biometric modalities
3.2. Facial region modalities
Image acquisition methods:
1) 2D
2) 3D
3) Facial thermograph
4) localization and segmentation
Biometric modalities
3.2. Facial region modalities
Advantage:
1)
The most nature
2)
non-intrusive
3)
contactless
higher public acceptance
Disadvantage:
1)
cosmetics
2)
plastic surgery
3)
person's face may change or be changed over time
4)
expensive imaging hardware
5)
illumination conditions, pose variations , ageing conditions
6)
poor recognition accuracy
Biometric modalities
3.3. Ocular region modalities
1) Iris
2) Retina
3) Sclera
Biometric modalities
3.3. Ocular region modalities
Biometric modalities
3.3. Ocular region modalities
Image acquisition methods:
1) infra-red light(retina, sclera )
2) illuminating human eye with near infra-red light or in visible wavelength
light(iris)
Biometric modalities
3.3. Ocular region modalities
Advantage:
1)
Highly accurate (higher uniqueness)
2)
Highly reliable
3)
Well protected
4)
Stable
5)
Almost impossible to forge
Disadvantage:
1)
synthetic iris images (need iris codes )
2)
intrusive (retina)
Biometric modalities
3.4. Medico-chemical biometrics
1) Body odor → not realized yet
2) Deoxyribonucleic Acid(DNA)
3) Heart sound
4) Electrocardiogram (ECG)
Biometric modalities
3.4. Medico-chemical biometrics
Image acquisition methods:
1) Specialized medical/chemical sensors
Samples from blood, hair, ear wax, dental floss and finger nail clippings(DNA)
Different organic compounds(body odor)
Biometric modalities
3.4. Medico-chemical biometrics
Advantage:
1)
The Most accurate (DNA)
Disadvantage:
1)
Intrusive
2)
Privacy issues
3)
Physical contact with sensors
4)
Requirement of skilled operators
5)
Full cooperation from the subjects
6)
Dependence over human medical and emotional states
Biometric modalities
3.5. Behavioral biometrics
1) Keystroke Dynamics
2) Voice
3) Signature
4) Gait
Biometric modalities
3.5. Behavioral biometrics
Biometric modalities
3.5. Behavioral biometrics
Acquisition methods:
1) Video
2) Sound Recording
3) Electronic whiteboard
Biometric modalities
3.5. Behavioral biometrics
Advantage:
1)
Easily for acquisition
Disadvantage:
1)
Dynamics
2)
Mimicking
Biometric modalities
3.6. Soft biometrics
1) Gender
2) Ethnicity
3) Height
4) Weight
5) Skin color
6) Eye color
7) Hair color
8) SMT(scars, marks and tattoos)
Biometric modalities
3.7. Application perspectives
Multi-modal biometrics
Multi-modal biometrics
Instead of the tremendous advances in biometric technology, the recognition
systems based on the measurement of single modality can not guarantee 100%
accuracy. This is due to influence of several factors.
1) Noisy data
2) Intra-class variations
3) Distinctiveness
4) Non-universality
5) Spoof attacks
Multi-modal biometrics
4.1. Sources of information
According to the nature of information sources, a multi-modal biometric system
can be classified into following categories: [23,275,276]
1) 4.1.1. Multi-sensor systems
2) 4.1.2. Multi-algorithm systems
3) 4.1.3. Multi-instance systems
4) 4.1.4. Multi-sample systems
5) 4.1.5. Multi-modal systems
Multi-modal biometrics
4.2. Modes of operations
A multi-modal biometric system functions in two modes:
1) Serial/cascaded mode
2) Parallel mode
Multi-modal biometrics
4.3. Fusion levels
The multiple biometric evidences acquired from different sources can be
combined together at different levels:
1) Sensor level
2) Feature level
3) Matching score level
4) Decision level
Multi-modal biometrics
4.3. Fusion levels
Multi-modal biometrics
4.3. Fusion levels
Multi-modal biometrics
4.3. Fusion levels
Biometrics prospects
Biometrics prospects
The increasing interest from the government and private
stakeholders to adopt biometric based identity management
systems prove the efficacy of such systems over the
knowledge and possession based systems.
Biometrics prospects
Biometrics prospects
Biometrics prospects
Conclusion
Conclusion
Reliable Identification is a crucial requirement in a wide variety
of systems & different scenarios.
Traditional cryptographic methods do not offer practical
identification capabilities.
As an alternative, reliable identification, very often referred as
“biometrics” provide better solutions to high security demands
of the present day.
A wide variety of biometric characteristics have been discovered
and tested in recent decades.
Conclusion
In this paper, we provided an overview of the existing
biometric technologies along with their composition,
classification and performance evaluation indicators.
This paper also provides an in- depth overview followed by
detailed discussion over different biometric attributes along
with their potential advantages and challenges.
In terms of multiple attributes, careful selection is the key
point to success since selecting the modalities belonging to
one region may not be a good choice
Conclusion
Furthermore, we also stress the importance of reliable
template protection strategies since the development of
artificial gummy fingers and synthetic irises may lead to
questions regarding the reliability of the most secure
biometric signatures so far.
Conclusion
Despite the challenges, the market trend presented in the
paper portrays a keen interest in biometric solutions to a
number of identity management tasks. The large
deployment of such systems in private as well as the
stringent security environments is evident from the
exemplary evidences produced here. Conclusively, the
increasing trend of interest from government and private
stake- holders promises a bright future to the science of
biometrics.
Thank you for Listening