Face recognition using arm 7

FACE RECOGNITION USING ARM7

Technical seminar on

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.

CONTENTS :

1. Introduction

2. Related work

3. Implementation

4. Methodology

5. System test

6. Experiment analysis

7. Advantages

8. Disadvantage

9. Conclusion

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.

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.

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.

METHODOLOGY OF MAIN ALGORITHM:

SYSTEM TEST :

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.

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.

DISADVANTAGES:

Face recognition systems cant tell the

difference between identical twins.

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

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.

QUERIES

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