01-09-2014, 12:56 PM
Face Recognition Technology On Seminar Report
[attachment=67503]
INTRODUCTION
The information age is quickly revolutionizing the way transactions are completed. Everyday actions are increasingly being handled electronically, instead of with pencil and paper or face to face. This growth in electronic transactions has resulted in a greater demand for fast and accurate user identification and authentication. Access codes for buildings, banks accounts and computer systems often use PIN's for identification and security clearences.
Using the proper PIN gains access, but the user of the PIN is not verified. When credit and ATM cards are lost or stolen, an unauthorized user can often come up with the correct personal codes. Despite warning, many people continue to choose easily guessed PIN's and passwords: birthdays, phone numbers and social security numbers. Recent cases of identity theft have hightened the nee for methods to prove that someone is truly who he/she claims to be.
Face recognition technology may solve this problem since a face is undeniably connected to its owner expect in the case of identical twins. Its nontransferable. The system can then compare scans to records stored in a central or local database or even on a smart card.
ABSTRACT
Wouldn’t you love to replace password based access control to avoid having to reset forgotten password and worry about the intergrity of your system? Wouldn’t you like to rest secure in comfort that your healthcare system does not merely on your social security number as proof of your identity for granting access to your medical records?
Because each of these questions is becoming more and more important, access to a reliable personal identification is becoming increasingly essential .Conventional method of identification based on possession of ID cards or exclusive knowledge like a social security number or a password are not all together reliable. ID cards can be lost forged or misplaced; passwords can be forgotten or compromised. But a face is undeniably connected to its owner. It cannot be borrowed stolen or easily forged
What are 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’s identity. Biometrics can measure both physiological and behavioral characteristics. Physiological biometrics (based on measurements and data derived from direct measurement of a part of the human body) include:
• Finger-scan
• Facial Recognition
• Iris-scan
• Retina-scan
• Hand-scan
Behavioral biometrics (based on measurements and data derived from an action) include:
• Voice-scan
• Signature-scan
• Keystroke-scan
Why we choose face recognition over other biometric?
There are a number reasons to choose face recognition. This includes the following
1. It requires no physical inetraction on behalf of the user.
2. It is accurate and allows for high enrolment and verification rates.
3. It does not require an expert to interpret the comparison result.
4. It can use your existing hardware infrastructure, existing camaras and image capture devices will work with no problems.
5. It is the only biometric that allow you to perform passive identification in a one to many environment (eg: identifying a terrorist in a busy Airport terminal
FACE RECOGNITION
THE FACE
The face is an important part of who you are and how people identify you. Except in the case of identical twins, the face is arguably a person's most unique physical characteristics. While humans have the innate ability to recognize and distinguish different faces for millions of years , computers are just now catching up.
For face recognition there are two types of comparisons .the first is verification. This is where the system compares the given individual with who that individual says they are and gives a yes or no decision. The second is identification. This 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:
• capture: a physical or behavioural sample is captured by the system during enrollment and also in identification or verification process.
• Extraction: unique data is extracted from the sample and a template is created.
• Comparison: the template is then compared with a new sample.
• Match/non match : the system decides if the features extracted from the new sample are a match or a non match.
Face recognition technology analyze the unique shape ,pattern and positioning of the facial features. Face recognition is very complex technology and is largely software based. This Biometric Methodology establishes the analysis framework with tailored algorithms for each type of biometric device. Face recognition starts with a picture, attempting to find a person in the image. This can be accomplished using several methods including movement, skin tones, or blurred human shapes. The face recognition system locates the head and finally the eyes of the individual. A matrix is then developed based on the characteristics of the individual’s face. The method of defining the matrix varies according to the algorithm (the mathematical process used by the computer to perform the comparison). This matrix is then compared to matrices that are in a database and a similarity score is generated for each comparison.
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. At an instant there will be large number of picture details existing simultaneously each representing the level of brightness of the scene to be reproduced. In other words the picture information is a function of two variables: time and space. Therefore it would require infinite number of channels to transmit optical information corresponding to picture elements simultaneously. There are practical difficulty in transmitting all information simultaneously so we use a method called scanning.
Here the conversion of optical information to electrical form and its transmission is carried out element by element one at a time in a sequential manner to cover the entire image. A TV camera converts optical information into electrical information, the amplitude of which varies in accordance with variation of brightness.
An optical image of the scene to be transmitted is focused by lense assembly on the rectangular glass plate of the camera tube. The inner side of this has a transparent coating on which is laid a very thin layer of photoconductive material. The photolayer has very high resistance when no light is falling on it but decreases depending on the intensity of light falling on it. An electron beam is formed by an electron gun in the TV camera tube. This beam is used to pick up the picture information now avilable on the target plate of varying resistace at each point.
COMPONENTS OF FACE RECOGNITION SYSTEMS
• An automated mechanism that scans and captures a digital or an analog image of a living personal characteristics.(enrollment module)
• Another entity which handles compression, processing, storage and compression of the captured data with stored data (database)
• The third interfaces with the application system ( identification module)
User interface captures the analog or digital image of the person's face. In the enrollment module the obtained sample is preprocessed and analyzed. This analyzed data is stored in the database for the purpose of future comparison.
The database compresses the obtained sample and stores it. It should have retrival property also that is it compares all the stored sample with the newly obtained sample and retrives the matched sample for the purpose of verification by the user and determine whether the match declared is right or wrong.
The verification module also consists of a preprocessing system. Verification means the system checks as to who the person says he or she is and gives a yes or no decision. In this module the newly obtained sample is preprocessed and compared with the sample stored in the database. The decision is taken depending on the match obtained from the database. Correspondingly the sample is accepted or rejected
HOW FACE RECOGNITION SYSTEMS WORK
An example
Visionics, company based in a New Jersey is one of the many developers of facial recognition technology. The twist to its particular software, Face it is that it can pick someone's face from the rest of the scene and compare it to a database full of stored images. In order for this software to work, it has to know what a basic face looks like. Facial recognition software is based on the ability to first recognize faces, which is a technological feat in itself and then measure the various features of each face.
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. Visionics defines these landmarks as nodal points. 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
• 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 faceprint. Only 14 to 22 nodal points are needed for faceit software to complete the recognition process.
THE SOFTWARE
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. Here is the basic process that is used by the Faceit system to capture and compare images
Detection
When the system is attached to a video surveillance system, the recognition software searches the field of view of a video camera for faces. If there is a face in the view, it is detected within a fraction of a second. A multi-scale algorithm is used to search for faces in low resolution. (An algorithm is a program that provides a set of instructions to accomplish a specific task). The system switches to a high-resolution search only after a head-like shape is detected
Matching
The newly acquired facial data is compared to the stored data and (ideally) linked to at least one stored facial representation. The heart of the FaceIt facial recognition system is the Local Feature Analysis (LFA) algorithm. This is the mathematical technique the system uses to encode faces. The system maps the face and creates a faceprint, a unique numerical code for that face. Once the system has stored a faceprint, it can compare it to the thousands or millions of faceprints stored in a database. Each faceprint is stored as an 84-byte file. Using facial recognition software, police can zoom in with cameras and take a snapshot of a face.
The system can match multiple faceprints at a rate of 60 million per minute from memory or 15 million per minute from hard disk. As comparisons are made, the system assigns a value to the comparison using a scale of one to 10. If a score is above a predetermined threshold, a match is declared. The operator then views the two photos that have been declared a match to be certain that the computer is accurate
APPLICATIONS
The natural use of face recognition technology is the replacement of PIN, physical tokens or both needed in automatic authorization or identification schemes. Additional uses are automation of human identification or role authentication in such cases where assistance of another human needed in verifying the ID cards and its beholder.
There are numerous applications for face recognition technology:
CONCLUSION
Face recognition technologies have been associated generally with very costly top secure applications. Today the core technologies have evolved and the cost of equipments is going down dramatically due to the intergration and the increasing processing power. Certain application of face recognition technology are now cost effective, reliable and highly accurate. As a result there are no technological or financial barriers for stepping from the pilot project to widespread deployment.
[attachment=67503]
INTRODUCTION
The information age is quickly revolutionizing the way transactions are completed. Everyday actions are increasingly being handled electronically, instead of with pencil and paper or face to face. This growth in electronic transactions has resulted in a greater demand for fast and accurate user identification and authentication. Access codes for buildings, banks accounts and computer systems often use PIN's for identification and security clearences.
Using the proper PIN gains access, but the user of the PIN is not verified. When credit and ATM cards are lost or stolen, an unauthorized user can often come up with the correct personal codes. Despite warning, many people continue to choose easily guessed PIN's and passwords: birthdays, phone numbers and social security numbers. Recent cases of identity theft have hightened the nee for methods to prove that someone is truly who he/she claims to be.
Face recognition technology may solve this problem since a face is undeniably connected to its owner expect in the case of identical twins. Its nontransferable. The system can then compare scans to records stored in a central or local database or even on a smart card.
ABSTRACT
Wouldn’t you love to replace password based access control to avoid having to reset forgotten password and worry about the intergrity of your system? Wouldn’t you like to rest secure in comfort that your healthcare system does not merely on your social security number as proof of your identity for granting access to your medical records?
Because each of these questions is becoming more and more important, access to a reliable personal identification is becoming increasingly essential .Conventional method of identification based on possession of ID cards or exclusive knowledge like a social security number or a password are not all together reliable. ID cards can be lost forged or misplaced; passwords can be forgotten or compromised. But a face is undeniably connected to its owner. It cannot be borrowed stolen or easily forged
What are 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’s identity. Biometrics can measure both physiological and behavioral characteristics. Physiological biometrics (based on measurements and data derived from direct measurement of a part of the human body) include:
• Finger-scan
• Facial Recognition
• Iris-scan
• Retina-scan
• Hand-scan
Behavioral biometrics (based on measurements and data derived from an action) include:
• Voice-scan
• Signature-scan
• Keystroke-scan
Why we choose face recognition over other biometric?
There are a number reasons to choose face recognition. This includes the following
1. It requires no physical inetraction on behalf of the user.
2. It is accurate and allows for high enrolment and verification rates.
3. It does not require an expert to interpret the comparison result.
4. It can use your existing hardware infrastructure, existing camaras and image capture devices will work with no problems.
5. It is the only biometric that allow you to perform passive identification in a one to many environment (eg: identifying a terrorist in a busy Airport terminal
FACE RECOGNITION
THE FACE
The face is an important part of who you are and how people identify you. Except in the case of identical twins, the face is arguably a person's most unique physical characteristics. While humans have the innate ability to recognize and distinguish different faces for millions of years , computers are just now catching up.
For face recognition there are two types of comparisons .the first is verification. This is where the system compares the given individual with who that individual says they are and gives a yes or no decision. The second is identification. This 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:
• capture: a physical or behavioural sample is captured by the system during enrollment and also in identification or verification process.
• Extraction: unique data is extracted from the sample and a template is created.
• Comparison: the template is then compared with a new sample.
• Match/non match : the system decides if the features extracted from the new sample are a match or a non match.
Face recognition technology analyze the unique shape ,pattern and positioning of the facial features. Face recognition is very complex technology and is largely software based. This Biometric Methodology establishes the analysis framework with tailored algorithms for each type of biometric device. Face recognition starts with a picture, attempting to find a person in the image. This can be accomplished using several methods including movement, skin tones, or blurred human shapes. The face recognition system locates the head and finally the eyes of the individual. A matrix is then developed based on the characteristics of the individual’s face. The method of defining the matrix varies according to the algorithm (the mathematical process used by the computer to perform the comparison). This matrix is then compared to matrices that are in a database and a similarity score is generated for each comparison.
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. At an instant there will be large number of picture details existing simultaneously each representing the level of brightness of the scene to be reproduced. In other words the picture information is a function of two variables: time and space. Therefore it would require infinite number of channels to transmit optical information corresponding to picture elements simultaneously. There are practical difficulty in transmitting all information simultaneously so we use a method called scanning.
Here the conversion of optical information to electrical form and its transmission is carried out element by element one at a time in a sequential manner to cover the entire image. A TV camera converts optical information into electrical information, the amplitude of which varies in accordance with variation of brightness.
An optical image of the scene to be transmitted is focused by lense assembly on the rectangular glass plate of the camera tube. The inner side of this has a transparent coating on which is laid a very thin layer of photoconductive material. The photolayer has very high resistance when no light is falling on it but decreases depending on the intensity of light falling on it. An electron beam is formed by an electron gun in the TV camera tube. This beam is used to pick up the picture information now avilable on the target plate of varying resistace at each point.
COMPONENTS OF FACE RECOGNITION SYSTEMS
• An automated mechanism that scans and captures a digital or an analog image of a living personal characteristics.(enrollment module)
• Another entity which handles compression, processing, storage and compression of the captured data with stored data (database)
• The third interfaces with the application system ( identification module)
User interface captures the analog or digital image of the person's face. In the enrollment module the obtained sample is preprocessed and analyzed. This analyzed data is stored in the database for the purpose of future comparison.
The database compresses the obtained sample and stores it. It should have retrival property also that is it compares all the stored sample with the newly obtained sample and retrives the matched sample for the purpose of verification by the user and determine whether the match declared is right or wrong.
The verification module also consists of a preprocessing system. Verification means the system checks as to who the person says he or she is and gives a yes or no decision. In this module the newly obtained sample is preprocessed and compared with the sample stored in the database. The decision is taken depending on the match obtained from the database. Correspondingly the sample is accepted or rejected
HOW FACE RECOGNITION SYSTEMS WORK
An example
Visionics, company based in a New Jersey is one of the many developers of facial recognition technology. The twist to its particular software, Face it is that it can pick someone's face from the rest of the scene and compare it to a database full of stored images. In order for this software to work, it has to know what a basic face looks like. Facial recognition software is based on the ability to first recognize faces, which is a technological feat in itself and then measure the various features of each face.
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. Visionics defines these landmarks as nodal points. 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
• 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 faceprint. Only 14 to 22 nodal points are needed for faceit software to complete the recognition process.
THE SOFTWARE
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. Here is the basic process that is used by the Faceit system to capture and compare images
Detection
When the system is attached to a video surveillance system, the recognition software searches the field of view of a video camera for faces. If there is a face in the view, it is detected within a fraction of a second. A multi-scale algorithm is used to search for faces in low resolution. (An algorithm is a program that provides a set of instructions to accomplish a specific task). The system switches to a high-resolution search only after a head-like shape is detected
Matching
The newly acquired facial data is compared to the stored data and (ideally) linked to at least one stored facial representation. The heart of the FaceIt facial recognition system is the Local Feature Analysis (LFA) algorithm. This is the mathematical technique the system uses to encode faces. The system maps the face and creates a faceprint, a unique numerical code for that face. Once the system has stored a faceprint, it can compare it to the thousands or millions of faceprints stored in a database. Each faceprint is stored as an 84-byte file. Using facial recognition software, police can zoom in with cameras and take a snapshot of a face.
The system can match multiple faceprints at a rate of 60 million per minute from memory or 15 million per minute from hard disk. As comparisons are made, the system assigns a value to the comparison using a scale of one to 10. If a score is above a predetermined threshold, a match is declared. The operator then views the two photos that have been declared a match to be certain that the computer is accurate
APPLICATIONS
The natural use of face recognition technology is the replacement of PIN, physical tokens or both needed in automatic authorization or identification schemes. Additional uses are automation of human identification or role authentication in such cases where assistance of another human needed in verifying the ID cards and its beholder.
There are numerous applications for face recognition technology:
CONCLUSION
Face recognition technologies have been associated generally with very costly top secure applications. Today the core technologies have evolved and the cost of equipments is going down dramatically due to the intergration and the increasing processing power. Certain application of face recognition technology are now cost effective, reliable and highly accurate. As a result there are no technological or financial barriers for stepping from the pilot project to widespread deployment.