Face recognition using arm 7

1. FACE RECOGNITION
USING ARM7
Technical seminar on

2. ABSTRACT :
The Embedded face recognition system is based on ARM
LPC2148 development board using Windows operating system,
detecting face by using HAAR features and then recognizing face by
using LBP features.

3. CONTENTS :
1. Introduction
2. Related work
3. Implementation
4. Methodology
5. System test
6. Experiment analysis
7. Advantages
8. Disadvantage
9. Conclusion

4. INTRODUCTION :
Face recognition technology is widely used biological
recognition technology.
In comparison with other identification methods,
face recognition has more convenient features.
This approach is based on ARM LPC2148 on Windows
operating system.

5. RELATED WORKS :
=> Real time Embedded face recognition for smart home.
=> Embedded car security system on face detection.
=> Human face recognition system using modified
PCA algorithm and ARM platform.

6. IMPLEMENTATION :
Face recognition is based on the LBP algorithm and PCA
with nearest neighbor classifier as the core algorithms of the
system identification.
Matlab is used as a front end process and keil code
runs at the back end in ARM7 Processor.

8. METHODOLOGY OF MAIN ALGORITHM:

9. SYSTEM TEST :

11. EXPERIMENTAL PROCESS :
Front end is written in matlab code in windows
operating system and back end is written in keil code.
The image that is to be matched is given in Front end
and the comparison is done in hardware where the program
is written in keil in ARM7.

13. ADVANTAGES :
1. Face recognition is easy to use and in many cases it can be
performed without a person even knowing.
2. Face recognition is also one of the most inexpensive
biometric in market & its prices should continue to go down.

14. DISADVANTAGES:
Face recognition systems cant tell the
difference between identical twins.

15. APPLICATIONS:
 Physical access control of buildings areas ,doors, cars or
net access.
Banking using ATM: The software is able to quickly
verify a customers face .
 Security systems

16. CONCLUSION:
Face recognition technologies have been associated
generally with very costly top secure applications. Today the core
technologies have evolved and the cost of equipment's is going
down dramatically due to the integrations and the increasing
processing power.
Certain application of face recognition technology
are now cost effective, reliable and highly accurate.

17. QUERIES