Face Recognition Proposal Presentation

Face Recognition

Under the Supervision of

Md. Shakir khan

Supervisor

Md. Nazmus Sadat

Co-supervisor

Group Members

Morshada AhkterMd. Atiqur Rahman Nurun Nahar Nisha

Outline

Biometrics

Why we choose face recognition over other biometric

Applications of face recognition

Face recognition

Working process

Our current working progress

Advantages & limitations

Future work

Biometrics

Fig: Biometrics

Why we choose face recognition

over other biometric

It requires no physical interaction on behalf of the user.

It is accurate and allows for high enrolment and verification rates.

It does not require an expert to interpret the comparison result.

It can use our existing hardware infrastructure, existing cameras and

image capture Devices will work with no problems

It is the only biometric that allow us to perform passive identificationin a one to many environments (e.g.: identifying a terrorist in a busy

Airport terminal)

Applications

Fig: Law Enforcement Fig: Security/Counterterrorism Fig: Immigration

Applications

Fig: Residential Security Fig: Banking using ATM Fig: Mobile unlocking

Face Recognition

Fig: Verification Fig: Identification

Advantages & Limitation

Advantages:

Its convenience and Social acceptability. all we need is our 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

price should continue to go down.

Limitation:

Face recognition systems can’t tell the difference between identical twins.

Working Process

Input image

Face detection

DatabaseFace

recognitionMatch/

not-match

Required Elements

Using software

MATLAB 8.1 (R2013a)

Hardware

USB PC Camera-168

Required products

Image Acquisition Toolbox

Image Processing Toolbox

Computer Vision System Toolbox

Our current status

Fig: Input Image

Face Detection

Algorithm used:

viola-jones algorithm (CascadeObjectDetector)

Working parameters:

detect FrontalFaceCART, LeftEye, RightEye, Mouth, and Nose simultaneously

Toolbox

Image Processing Toolbox

Computer Vision System Toolbox

Main functions:

detectFaceParts: Detects frontal faces with parts.

detectRotFaceParts: Detects faces with parts rotating an input image

Advantage:

The performance is improved compared to the default usage of the face detection

Face Parts Detection

Fig: Detected face part from group picture

Fig: Separated each of face part from this picture

Difference

Fig: Default viola-jones algorithm Fig: Modified viola-jones algorithm

Our Future work

After detection part we will match the detected image with a test

image.

We are also working to create a database for our input images.

Then we do the Recognition Part

Thank you