This document outlines a project on face recognition. It discusses biometrics and why face recognition was chosen over other methods. Applications of face recognition are presented for law enforcement, security, immigration, residential security, banking, and mobile unlocking. The working process of face recognition involves inputting an image, detecting the face, and recognizing the face by matching it to a database. The current progress includes detecting faces and face parts using a modified Viola-Jones algorithm. Future work will involve matching detected faces to images in a created database for recognition. Advantages of face recognition include convenience and limitations include inability to distinguish identical twins.

1. Face Recognition

2. Under the Supervision of
Md. Shakir khan
Supervisor
Md. Nazmus Sadat
Co-supervisor

3. Group Members
Morshada AhkterMd. Atiqur Rahman Nurun Nahar Nisha

4. 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

5. Biometrics
Fig: Biometrics

6. 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 identification
in a one to many environments (e.g.: identifying a terrorist in a busy
Airport terminal)

7. Applications
Fig: Law Enforcement Fig: Security/Counterterrorism Fig: Immigration

8. Applications
Fig: Residential Security Fig: Banking using ATM Fig: Mobile unlocking

9. Face Recognition
Fig: Verification Fig: Identification

10. 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.

11. Working Process
Input
image
Face
detection
Database
Face
recognition
Match/
not-match

12. 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

13. Our current status
Fig: Input Image

14. 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

15. Face Parts Detection
Fig: Detected face part from group picture
Fig: Separated each of face part from this picture

16. Difference
Fig: Default viola-jones algorithm Fig: Modified viola-jones algorithm

17. 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

18. Thank you