face recognition technology.ppt

                                                               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 forget.

Contents

1.           INTRODUCTION………………………………………………………4

2.           FACE RECOGNITION………………………….……………………..6

3.           CAPTURING OF IMAGE BY STANDARD VIDEO CAMERAS………………………………………………………………8

4.           COMPONENTS OF FACE RECOGNITION SYSTEM…………...10

5.           IMPLEMENTATION OF FACE RECOGNITION TECHNOLOGY……………………………………………………….12

6.           HOW FACE RECOGNITION SYSTEMS WORK -An example….14

7.           THE SOFTWARE…………………………………………………..…15

8.           ADVANTAGES AND DISADVANTAGES……………………...…..17

9.           APPLICATIONS……………………………………………………....18

10.      CONCLUSION……………….………………………………………..19

11.      REFERENCES………………………………………………………...20

                                                  1. 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.

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

A “biometric system” refers to the integrated hardware and software used to conduct biometric identification or verification.

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 interaction 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.

                                2.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 behavioral 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.                        Artificial intelligence is used to simulate human interpretation of faces. In order to increase the accuracy and adaptability , some kind of machine learning has to be implemented.

                      There are essentially two methods of capture. One is video imaging and the other is thermal imaging. Video imaging is more common as standard video cameras can be used. The precise position and the angle of the head and the surrounding lighting conditions may affect the system performance. The complete facial image is usually captured and a number of points on the face can then be mapped, position of the eyes, mouth and the nostrils as a example. More advanced technologies make 3-D map of the face which multiplies the possible measurements that can be made. Thermal imaging has better accuracy as it uses facial temperature variations caused by vein structure as the distinguishing traits.

	FACE RECOGNITION BLOCK DIAGRAM FIGURE 1

 

 

  3.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.

                      The electron beam is deflected by a pair of deflecting coils mounted on the glass envelope and kept mutually perpendicular to each other to achive scanning of the entire target area. The deflecting coils are fed seperately from two sweep oscillators, each operating at different frequencies. The magnetic deflection caused by current in one coil gives horizontal motion to the beam from left to right at a uniform rate and brings it back to the left side to commence the trace of the next line. The other coil is used to deflect the beam from top to bottom.

CAPTURING OF IMAGE BY STANDARD VIDEO CAMERAS

FIGURE 2

        4.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)

 

COMPONENTS OF FACE RECOGNITION SYSYTEM

Figure 3

                      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.

                      Instead of verification module we can make use of identification module. In this the sample is compared with all the other samples stored in the database. For each comparison made a match score is given. The decision to accept or reject the sample depends on this match score falling above or below a predetermined threshold.

5.IMPLEMENTATION OF FACE RECOGNITION TECHNOLOGY

                      The implementation of face recognition technology include the following four stages:

They are:-

·                     data acquisition

·                     input processing

·                     face image classification and

·                     decision making

Data acquisition:

                      The input can be recorded video of the speaker or a  still image. A sample of 1 sec duration consists of a 25 frame video sequence. More than one camera can be used to produce a 3D representation of the face and to protect against the usage of photographs to gain unauthorized access.

Input processing:

                      A pre-processing module locates the eye position and takes care of the surrounding lighting condition and colour variance. First the presence of faces or face in a scene must be detected. Once the face is detected, it must be localized and normalization process may be required to bring the dimensions of the live facial sample in alignment with the one on the template.

                      Some facial recognition approaches use the whole face while others concentrate on facial components and/ or regions(such as lips, eyes etc). the appearance

of the face can change considerably during speech and due to facial expressions. In particular the mouth is subjected to fundemental changes
but is also very important source for discriminating faces. So an approach to persons recognition is developed based on spatio-temporal modeling of features extracted from talking face. Models are trained specific to a persons speech articulate and the way that the person speaks. Person identification is performed by tracking mouth movements of the talking face and by estimating the likelyhood of each model of having generated the observed sequence of features. The model with the highest likelyhood is chosen as the recognized person.

                6.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.

        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.

They are:-

·        distance between the eyes

·        width of the nose

·        depth of the eye socket

·        cheekbones

·        jaw line

·        chin

                                       7.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.

Alignment:

                  Once a face is detected, the system determines the head's position, size and pose. A face needs to be turned at least 35 degrees toward the camera for the system to register it.

Normalization:-The image of the head is scaled and rotated so that it can be registered and mapped into an appropriate size and pose. Normalization is performed regardless of the head's location and distance from the camera. Light does not impact the normalization process.

Representation:-

                      The system translates the facial data into a unique code. This coding process allows for easier comparison of the newly acquired facial data to stored facial data.

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.

8.ADVANTAGES AND DISADVANTAGES

ADVANTAGES:

·        There are many benefits to face recognition systems such  as its convinence and social acceptability. All you need is your picture taken for it to work.

·        Face recognition is easy to use and in many cases it can be performed without a person even knowing.

·        Face recognition is also one of the most inexpensive biometric in the market and its prices should continue to go down.

·                     No advanced hardware required.

·               No physical contact.

·               No intrusion or delay.

·               Ideal for high traffic areas.

·               Hard to fool.

·               Replace guessable or insecure passwords.

             

DISADVANTAGES:

• Reliability is slightly lower.
• System fails for undistinguished features and large emotional changes.
• Tolerate variations in the face.

Face is not so unique as fingerprints and eye iris, so its recognition reliability is slightly lower. However, it is still suitable for many applications, taking into account its convenience for user. It can also be used together with fingerprint identification or another biometrical method for developing more security critical applications. Face recognition cannot be used for surveillance applications as it works only for frontal face images.                       

9.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:

Government Use:

1.       Law Enforcement: Minimizing victim trauma by narrowing mugshot searches, verifying identify for court records, and comparing school surveillance camera images to known child molesters.

1.      Security/Counterterrorism. Access control, comparing surveillance images to   known terrorists.

2.      Immigration: Rapid progression through Customs.

Commercial Use:

1.      Day Care: Verify identity of individuals picking up the children.

2.      Residential Security: Alert homeowners of approaching personnel.

3.      Voter verification: Where eligible politicians are required to verify  their identity during a voting process.

4.      Banking using ATM: The software is able to quickly verify a customers face.

10.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.

 

                                            11.REFERENCES

   1.      IEEE Intelligent Systems - May/June 2010

2.      WWW.FACEREG.COM

3.      WWW. IMAGESTECHNOLOGY.CO

   4..http://www.blogtoplist.com/rss/faceid

   5.http://en.wikipedia.org/wiki/faceregonitiontechnology