INTRODUCTION
FACE RECOGNITION
CAPTURING OF IMAGE BY STANDARD VIDEO CAMERAS
COMPONENTS OF FACE RECOGNITION SYSTEMS
IMPLEMENTATION OF FACE RECOGNITION TECHNOLOGY
PERFORMANCE
SOFTWARE
ADVANTAGES AND DISADVANTAGES
APPLICATIONS
CONCLUSION
A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source.
This slide is all about a detailed description of the Face Recognition System.
Face recognition system plays an important role when its comes to security, In this slide using of neural networking system for face recognition system has demonstrated.
A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source.
This slide is all about a detailed description of the Face Recognition System.
Face recognition system plays an important role when its comes to security, In this slide using of neural networking system for face recognition system has demonstrated.
Face Detection and Recognition System (FDRS) is a physical characteristics recognition technology, using the inherent physiological features of humans for ID recognition. The technology does not need to be carried about and will not be lost, so it is convenient and safe for use
This application was design with help of OpenCv and C#.
Facial recognition (or face recognition) is a type of bio-metric application that can identify a specific individual in a digital image by analysing and comparing patterns.
Face recognition software is based on the ability to first recognize faces, which is a technological feat in itself. If we look at the mirror, we can see that your face has certain distinguishable landmarks. These are the peaks and valleys that make up the different facial features.
This application take picture of your face and after storing it.
Then it start identifying all face which are store in database.
Humans often use faces to recognize individuals, and advancements in computing capability over the past few decades now enable similar recognitions automatically. Early facial recognition algorithms used simple geometric models, but the recognition process has now matured into a science of sophisticated mathematical representations and matching processes. Major advancements and initiatives in the past 10 to 15 years have propelled facial recognition technology into the spotlight. Facial recognition can be used for both verification and identification.
The slide was prepared on the purpose of presentation of our project face detection highlighting the basics of theory used and project details like goal, approach. Hope it's helpful.
Face Detection and Recognition System (FDRS) is a physical characteristics recognition technology, using the inherent physiological features of humans for ID recognition. The technology does not need to be carried about and will not be lost, so it is convenient and safe for use
This application was design with help of OpenCv and C#.
Facial recognition (or face recognition) is a type of bio-metric application that can identify a specific individual in a digital image by analysing and comparing patterns.
Face recognition software is based on the ability to first recognize faces, which is a technological feat in itself. If we look at the mirror, we can see that your face has certain distinguishable landmarks. These are the peaks and valleys that make up the different facial features.
This application take picture of your face and after storing it.
Then it start identifying all face which are store in database.
Humans often use faces to recognize individuals, and advancements in computing capability over the past few decades now enable similar recognitions automatically. Early facial recognition algorithms used simple geometric models, but the recognition process has now matured into a science of sophisticated mathematical representations and matching processes. Major advancements and initiatives in the past 10 to 15 years have propelled facial recognition technology into the spotlight. Facial recognition can be used for both verification and identification.
The slide was prepared on the purpose of presentation of our project face detection highlighting the basics of theory used and project details like goal, approach. Hope it's helpful.
Automated attendance system based on facial recognitionDhanush Kasargod
A MATLAB based system to take attendance in a classroom automatically using a camera. This project was carried out as a final year project in our Electronics and Communications Engineering course. The entire MATLAB code I've uploaded it in mathworks.com. Also the entire report will be available at academia.edu page. Will be delighted to hear from you.
Its a power point presentation on face recognition system . In the covid time biometrics is not a good option thats why we need a face recognition system
Biometric technology is a unique, measurement characteristic of human body like face and voice recognition. It is providing strong security for your personal information.
AI Approach for Iris Biometric Recognition Using a Median FilterNIDHI SHARMA
The Artificial Intelligence approach is used for Iris recognition by understanding the distinctive and measurable characteristics of the human body such as a person’s face, iris, DNA, fingerprints, etc. AI methods analyzed the attributes like iris images. Privacy and Security being a major concern nowadays, Recognition Technique can find numerous applications.
Facial Recognization
Introduction:
A type of biometric technology called facial recognition uses algorithms to recognize and
confirm a person's identity based on their facial traits. To generate a face template, the
system examines a person's distinctive facial features, such as the separation between their
eyes, the lines of their jawline, and the shape of their nose. The person's identity is then
verified by comparing this template to a database of pictures.
There are several uses for facial recognition technology, including:
Controlling access to guarded locations or seeing possible risks in public areas is a security
risk.
Advertising: to target customers based on their age, gender, and other demographic
characteristics.
Identifying and locating suspects, monitoring illegal activity, and assisting with
investigations.
The use of facial recognition has generated a great deal of discussion around the world due
to worries about accuracy, bias, and privacy. The advantages and disadvantages of facial
recognition will be explored in this article, along with some frequently asked questions
regarding this cutting-edge technology.
The advantages of facial recognition:
Numerous benefits of facial recognition technology make it a desirable alternative for
organizations, governments, and people in general. The following are some advantages of
facial recognition:
Greater Security:
Access to sensitive spaces like offices, labs, and data centers can be restricted using facial
recognition technology. Contrary to conventional security systems, which rely on users to
memorize and enter passwords or swipe cards, facial recognition technology can recognize
people automatically. This removes the possibility of having credentials lost or stolen, which
lowers the possibility of security breaches.
Facial recognition is helpful in public areas because it can spot possible dangers like
criminals or terrorists. Authorities can be immediately notified about people on watchlists or
with criminal histories by security cameras with facial recognition technology.
Convenience:
Technology for facial recognition is practical and simple to use. Passwords, ID cards, and
other tangible forms of identification are no longer required. For instance, all you have to do
to unlock your phone is stare at it. This makes facial recognition a well-liked option among
customers who value practicality and simplicity.
Marketing Perspectives:
Data on consumer behavior can also be gathered using facial recognition technologies.
Businesses can get crucial information about how customers respond to various items and
marketing by examining customer demographics and facial expressions. Then, by tailoring
marketing initiatives, this information can enhance client satisfaction.
Negative aspects of facial recognition:
Face recognition technology has a lot of advantages, but it also has a lot of disadvantages.
The following are some of the major drawbacks of facial recognition:
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2. INTRODUCTION
Facial recognition (or face recognition) is a type of biometric software
application that can identify a specific individual in a digital image by analyzing and
comparing patterns.
Facial recognition systems are commonly used for security purposes but are
increasingly being used in a variety of other applications. For example, Facebook uses
facial recognition software to help automate user tagging in photographs.
1. What are biometrics?
Ans: A biometric is a unique, measurable characteristic of a human being that can be
used to automatically recognize an individual or verify an individual identity. Biometrics
can measure both physiological and behavioral characteristics.
Physiological biometrics (based on measurements and data derived from direct the
human body) include:
a. Finger-scan ,
b. Facial Recognition,
c. Iris-scan ,
d. Retina-scan and
e. Hand-scan.
Behavioral biometrics (based on measurements and data derived from an action)
include:
a. Voice-scan ,
b. Signature-scan and
c. Keystroke-scan .
3. FACE RECOGNITION
The face is an important part of who you are and how people identify you.
For face recognition there are two types of comparisons.
The first is verification and the second is identification.
verification is where the system compares the given individual with who that
individual says they are and gives a yes or no decision..
identification is where the system compares the given individual to all the
Other individuals in the database and gives a ranked list of matches.
All identification or authentication technologies operate using the following
four stages:
1. Capture: A physical sample is captured by the system during enrollment and
also in identification or Verification process.
2. Extraction: unique data is extracted from the sample and a template is
created.
3. Comparison: the template is then compared with a new sample.
4. Match/Non match: the system decides if the features extracted from the
new
4. CAPTURING OF IMAGE BY STANDARD
VIDEO CAMERAS
The image is optical in characteristics and may be thought of as a collection of a
large number of bright and dark areas representing the picture details.
In other words the picture information is a function of two variables:
Time and Space.
It would require infinite number of channels to transmit optical information
corresponding to picture elements simultaneously. There is practical difficulty in
transmitting all information simultaneously so we use a method called scanning.
5. COMPONENTS OF FACE RECOGNITION
SYSTEMS
The 3 main components of face recognition systems, they are as follows
Enrollment module,
Database and
Identification module.
6. HOW FACE RECOGNITION SYSTEMS WORK
Facial recognition software is based on the ability to first recognize faces, which
is a technological feat in itself.
If you look at the mirror, you can see that your face has certain distinguishable
landmarks. These are the peaks and valleys that make up the different facial features.
There are about 80 nodal points on a human face. Here are few nodal points that
are measured by the software.
• Distance between the eyes
• Width of the nose
• Depth of the eye socket
• Cheekbones
• Jaw line and
• Chin
These nodal points are measured to create a numerical code, a string of numbers
that represents a face in the database. This code is called face print.
Only 14 to 22 nodal points are needed for faceit software to complete the
recognition process
7. IMPLEMENTATION OF FACE RECOGNITION
TECHNOLOGY
The implementation of face recognition technology includes the following four
stages:
1. Data acquisition,
2. Input processing ,
3. Face image classification and
4. Decision making .
8. PERFORMANCE
1. False rejection rates (FRR) :
The probability that a system will fail to identify an enrollee. It is also called
type 1 error rate.
FRR= NFR/NEIA
Where
FRR= false rejection rates
NFR= number of false rejection rates
NEIA= number of enrollee identification attempt
2. False acceptance rate (FAR) :
The probability that a system will incorrectly identify an individual or will fail
to reject an imposter. It is also called as type 2 error rate
FAR= NFA/NIIA
Where
FAR= false acceptance rate
NFA= number of false acceptance
NIIA= number of imposter identification attempts
9. SOFTWARES
Facial recognition software falls into a larger group of technologies known as
biometrics. Facial recognition methods may vary, but they generally involve a series of
steps that serve to capture, analyze and compare your face to a database of stored images.
The basic process that is used by the Faceit system to capture and compare
images:
1. Detection,
2. Alignment,
3. Normalization,
4. Representation and
5. Matching.
10. Advantages :
1. There are many benefits to face recognition systems such as its convenience
and Social acceptability. All you need is your picture taken for it to work.
2. Face recognition is easy to use and in many cases it can be performed without
a Person even knowing.
3. Face recognition is also one of the most inexpensive biometric in the market
and Its price should continue to go down.
ADVANTAGES AND DISADVANTAGES
Disadvantage:
1. Face recognition systems cant tell the difference between identical twins.
11. There are numerous applications for face recognition technology:
Commercial Use:
a. Day Care: Verify identity of individuals picking up the children.
b. Residential Security: Alert homeowners of approaching personnel
c. Voter verification: Where eligible politicians are required to verify
their identity during a voting process.
d. Banking using ATM: The software is able to quickly verify a customer.
APPLICATIONS
12. Face recognition technologies have been associated generally with very costly
top secure applications. Today the core technologies have evolved and the cost of
equipment is going down dramatically due to the integration and the increasing
processing power. Certain applications of face recognition technology are now cost
effective, reliable and highly accurate.
CONCLUSION
13. THANK YOU
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