This document discusses face recognition technology. It begins by defining facial recognition as a type of biometric software that can identify individuals by analyzing patterns in digital images. It then discusses the components and process of how face recognition systems work, including capturing images, extracting nodal point data to create a face print, storing prints in a database, and matching new images to those in the database. The document also covers performance metrics, software, applications, advantages and disadvantages, and concludes that face recognition technology is becoming more cost effective and accurate for various commercial and security uses.
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.
NEC NEOFACE- Biometric Face Recognition SystemNECIndia
NEC NeoFace combines an extracted analysis of the eyes with a
detailed determination of facial feature, using a GLVQ based multiple matching face recognition system.Providing a reliable verification solution.
This presentation of about Face Recognition. you can learn about face recognition history, how's it is work traditional and in technical way, introduction of some face recognition software and devices. we don't add any face recognition algorithm in presentation.
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.
NEC NEOFACE- Biometric Face Recognition SystemNECIndia
NEC NeoFace combines an extracted analysis of the eyes with a
detailed determination of facial feature, using a GLVQ based multiple matching face recognition system.Providing a reliable verification solution.
This presentation of about Face Recognition. you can learn about face recognition history, how's it is work traditional and in technical way, introduction of some face recognition software and devices. we don't add any face recognition algorithm in presentation.
Facial Recognition: The Science, The Technology, and Market ApplicationsInvestorideas.com
Ravi Das
Technical Writer
BiometricNews.net
Ravi is a technical writer for BiometricNews.net, Inc., and independent news and information business about the Biometrics Industry. Ravi has been involved in Biometrics for 10+ years. He holds a BS in Ag Econ from Purdue, and MS in Ag Bus Economics (International Trade) from Southern Illinois University, Carbondale, and an MBA (MIS) from Bowling Green State University.
Facial recognition is a form of computer vision that uses faces to attempt to identify a person or verify a person’s claimed identity. Regardless of specific
VisageCloud - Face Recognition meets Big Data.Bogdan Bocse
Visage Cloud merges state-of-the-art deep learning algorithms for face recognition and classification with data querying, tagging and querying techniques so as to empower you to leverage the full value of your data.
Face recognition meets big data. In cloud or on-premise.
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
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.
Presentation on Face Recognition: A facial recognition is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source.
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.
Facial Recognition: The Science, The Technology, and Market ApplicationsInvestorideas.com
Ravi Das
Technical Writer
BiometricNews.net
Ravi is a technical writer for BiometricNews.net, Inc., and independent news and information business about the Biometrics Industry. Ravi has been involved in Biometrics for 10+ years. He holds a BS in Ag Econ from Purdue, and MS in Ag Bus Economics (International Trade) from Southern Illinois University, Carbondale, and an MBA (MIS) from Bowling Green State University.
Facial recognition is a form of computer vision that uses faces to attempt to identify a person or verify a person’s claimed identity. Regardless of specific
VisageCloud - Face Recognition meets Big Data.Bogdan Bocse
Visage Cloud merges state-of-the-art deep learning algorithms for face recognition and classification with data querying, tagging and querying techniques so as to empower you to leverage the full value of your data.
Face recognition meets big data. In cloud or on-premise.
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
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.
Presentation on Face Recognition: A facial recognition is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source.
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.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
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.
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
HUMAN FACE RECOGNITION USING IMAGE PROCESSING PCA AND NEURAL NETWORKijiert bestjournal
Security and authentication of a person is a vital part of any business. There are many techniques use d for this purpose. One of technique is human face recognition . Human Face recognition is an effective means of authenticating a person. The benefit of this approa ch is that,it enables us to detect changes in the face pattern of an individual to substantial extent. The recognition s ystem can tolerate local variations in the face exp ression of an individual. Hence Human face recognition can be use d as a key factor in crime detection mainly to iden tify criminals. There are several approaches to Human fa ce recognition of which Image Processing Principal Component Analysis (PCA) and Neural Networks have been includ ed in our project. The system consists of a databas e of a set of facial patterns for each individual. The charact eristic features called �eigenfaces� are extracted from the stored images using which the system is trained for subseq uent recognition of new images.
Biometric technology is a unique, measurement characteristic of human body like face and voice recognition. It is providing strong security for your personal information.
Similar to Face recognition Technology By Rohit (20)
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Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
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• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
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Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
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Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
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.
Biometrics :
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
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 face it 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 Face it 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