Vision-Based Vision-Based Biometric Biometric

Authentication Authentication SystemSystem

by Padraic o hIarnainby Padraic o hIarnain

Final Year Project Final Year Project PresentationPresentation

Vision-Based Biometric Vision-Based Biometric Authentication SystemAuthentication System

Face Detection

Authentication

Input from Camera

Face Recognition

Why make a Vision-Based Why make a Vision-Based Biometric Authentication Biometric Authentication

System?System? Advantages over PIN/password method:Advantages over PIN/password method:

More secureMore secure No passwords to rememberNo passwords to remember Less tediousLess tedious

PracticalPractical Advances in image processing techniquesAdvances in image processing techniques Low cost of digital imaging hardwareLow cost of digital imaging hardware

Vision-Based Biometric Vision-Based Biometric Authentication Authentication DevelopmentDevelopment

Face Detection

Face Detection

with Camera

Authentication System

Face Detection

Authentication System

Face Recognition

Face Recognition Authentication System

Add New User Utility

Integration of Entire System

Face DetectionFace Detection

Determines the location of a face in an Determines the location of a face in an imageimage

Involves capturing images in real-time Involves capturing images in real-time from a camera and then determining from a camera and then determining whether or not the image contains facial whether or not the image contains facial featuresfeatures

Statistical approach originally developed Statistical approach originally developed by Paul Viola and Michael Jonesby Paul Viola and Michael Jones

Face Detection and the Face Detection and the Viola-Jones AlgorithmViola-Jones Algorithm

Uses simple Haar-like features and a Uses simple Haar-like features and a cascade of boosted tree classifiers.cascade of boosted tree classifiers.

Haar-like features are calculated for Haar-like features are calculated for the images and then passed through the images and then passed through a cascade of boosted classifiers in a cascade of boosted classifiers in order to determine if they are facial order to determine if they are facial features.features.

Face Detection and the Face Detection and the Viola-Jones AlgorithmViola-Jones Algorithm

Calculate the Haar-like features. Using a SAT Calculate the Haar-like features. Using a SAT (Summed Area Table) to speed up the process.(Summed Area Table) to speed up the process.

Computed feature value is passed through a Computed feature value is passed through a simple classifier. This classifier responds with a simple classifier. This classifier responds with a +1 for a pass or a -1 for a fail.+1 for a pass or a -1 for a fail.

Chain a bunch of weak classifiers together into Chain a bunch of weak classifiers together into a more complex classifier known as a boosted a more complex classifier known as a boosted classifier.classifier.

Create a cascade of boosted classifiers.Create a cascade of boosted classifiers. The image contains a face if it passes all The image contains a face if it passes all

classifiers.classifiers.

Face Detection ProgramFace Detection Program

The Face Detection program is The Face Detection program is implemented using the OpenCV library.implemented using the OpenCV library.

Program that processes images from a Program that processes images from a camera in real-time and then detects if any camera in real-time and then detects if any face objects are present in that image.face objects are present in that image. Pass the classifier locationPass the classifier location Pass the input typePass the input type Convert input image from colour to a greyscale Convert input image from colour to a greyscale

image and then resize it to a smaller image.image and then resize it to a smaller image. Check the image for face objects. Use Check the image for face objects. Use

“cvHaarDetectObjects”.“cvHaarDetectObjects”.

Face Detection ProgramFace Detection Program

Camera ImplementationCamera Implementation TestingTesting

Tested with different face images.Tested with different face images. Tested with non-face images.Tested with non-face images. Tested with different objects in front of Tested with different objects in front of

camera; faces and non-faces.camera; faces and non-faces. ImprovementsImprovements

Changed camera settings.Changed camera settings.

Face Detection ResultsFace Detection Results

The end result of face detection. The The end result of face detection. The program worked every time.program worked every time.

AuthenticationAuthentication

Authentication SystemAuthentication System The process of authenticating a user.The process of authenticating a user. Integrating this process with a Integrating this process with a

Biometric system.Biometric system. Authentication System DevelopmentAuthentication System Development

Create a basic authentication system Create a basic authentication system based on file IO.based on file IO.

Implement this system with face Implement this system with face detection and face recognition.detection and face recognition.

Authentication and PAMAuthentication and PAM

PAM (Pluggable Authentication PAM (Pluggable Authentication Module)Module) Assimilates multiple low-level Assimilates multiple low-level

authentication systems into high-level authentication systems into high-level applications.applications.

PAM developmentPAM development Edit PAM configuration for the login and Edit PAM configuration for the login and

screensaver applications.screensaver applications. Create authentication modules for the Create authentication modules for the

login and screensaver applications.login and screensaver applications.

Authentication and PAMAuthentication and PAM

Login Authentication ModuleLogin Authentication Module The module reads a name from a file and The module reads a name from a file and

attempts to log that user on.attempts to log that user on. Authentication fails if there is no name or Authentication fails if there is no name or

the name is not a user name.the name is not a user name. Screensaver Authentication ModuleScreensaver Authentication Module

The module reads a name from a file and The module reads a name from a file and if that name is the same as the current if that name is the same as the current user then it authenticates the application.user then it authenticates the application.

Face Detection Face Detection Authentication SystemAuthentication System

Integrating Face Detection Program Integrating Face Detection Program with the Authentication Systemwith the Authentication System Face Detection program changed so it Face Detection program changed so it

writes a default user name to a file writes a default user name to a file every time a face is detected.every time a face is detected.

Integrating Face Detection Program Integrating Face Detection Program with the Start-up protocolwith the Start-up protocol Included Face Detection program in a Included Face Detection program in a

run-level 5 script.run-level 5 script.

Face Detection Face Detection Authentication System Authentication System

ResultsResults TestingTesting

Ran the system for a few hours.Ran the system for a few hours. ResultResult

When a face is detected the PAM When a face is detected the PAM modules read in the default user name modules read in the default user name and use it in authentication. and use it in authentication. Authentication works with the Face Authentication works with the Face Detection Program.Detection Program.

Face RecognitionFace Recognition

Examination of facial features in an Examination of facial features in an image, recognising those features image, recognising those features and matching them to one of the and matching them to one of the many faces in the databasemany faces in the database

PCA (Principal Component Analysis) PCA (Principal Component Analysis) method of face recognition is used method of face recognition is used on the input image from the camera.on the input image from the camera.

Face Recognition and Face Recognition and PCAPCA

What is PCA?What is PCA? The process of extracting the most The process of extracting the most

relevant information contained in a face relevant information contained in a face and then building a computational and then building a computational model that best describes it.model that best describes it.

Why use PCA?Why use PCA? Process speedProcess speed Time limitationsTime limitations AccuracyAccuracy

Theory of PCATheory of PCA

Eigenvectors or Eigenfaces are Eigenvectors or Eigenfaces are obtained by training a set of face obtained by training a set of face images.images.

These Eigenvectors represent a basis of These Eigenvectors represent a basis of an Eigenspace in which every face is an Eigenspace in which every face is projected on.projected on.

Recognition is performed by comparing Recognition is performed by comparing the location of a face in the Eigenspace the location of a face in the Eigenspace with the location of known users.with the location of known users.

PCA ImplementationPCA Implementation

Implementation using OpenCVImplementation using OpenCV Create an Eigenspace using a set of training Create an Eigenspace using a set of training

faces.faces. Calculate the location of each face in the Calculate the location of each face in the

Eigenspace.Eigenspace. Calculate the location of the input image in the Calculate the location of the input image in the

Eigenspace.Eigenspace. Calculate the distance between the input image Calculate the distance between the input image

and every other face in the training set.and every other face in the training set. If the distance is under a certain threshold than If the distance is under a certain threshold than

print that user’s name to an output file.print that user’s name to an output file.

New User UtilityNew User Utility

Prompts for a user namePrompts for a user name Creates a user profile under that Creates a user profile under that

namename Capture image from camera of the Capture image from camera of the

new usernew user Save the new user image into the Save the new user image into the

database of user facesdatabase of user faces Store new user name in a text file for Store new user name in a text file for

integration with face recognitionintegration with face recognition

Vision-Based Biometric Vision-Based Biometric Authentication SystemAuthentication System

Reads user names from a file.Reads user names from a file. Loads corresponding face images.Loads corresponding face images. Prepare all images for face analysis.Prepare all images for face analysis. Calculates Eigenvectors using these face Calculates Eigenvectors using these face

images.images. Compares input image with the faces in Compares input image with the faces in

the user database.the user database. If an input face is very similar to a user If an input face is very similar to a user

face then that user is authenticated.face then that user is authenticated.

ConclusionConclusion

What I’ve learnedWhat I’ve learned Improved knowledge of Linux, C Improved knowledge of Linux, C

programming and writing scripts.programming and writing scripts. Improved knowledge of image Improved knowledge of image

processing techniques; especially in the processing techniques; especially in the field of biometrics.field of biometrics.

What I’ve completedWhat I’ve completed A fully functional vision-based biometric A fully functional vision-based biometric

authentication system.authentication system.

QuestionsQuestions

Thank you, Thank you, Goodbye!Goodbye!