Existing Work:
In the Existing System, it was developed on a ARM 9 Based Device is very have very low hardware specifications , due to which open cv based image processing applications will run at a very slow rate.
As well the face recognition used in this implementation where using a predefined database images only.
Proposed Work:
In the proposed Face Recognition using Image Processing Platform on ARM11 work ware going to implement the face recognition on a live USB camera streaming over a powerful ARM 11 architecture based board using a Debian based Linux operating system ( Raspbian OS) and OpenCV image processing library ported on it.
Here, a USB camera will be interface to the board, the system will have 2 modes i.e. Training & Recognition. In training mode, will capture live images of the face to be recognized and train it accordingly with a specific user id, in recognition mode the system will recognize the face if it is authenticated then will turn on the motor or else no action will be done.
BLOCK DIAGRAM
Hardware:
ARM11, USB Camera, Power supply.
Software:
OS: Embedded Linux, Language: C/ C++, IDE: Qt Creator, OpenCV Image Processing Library
Applications:
Home Security, Locker Authentication, face recognition
Advantages:
• Low Cost of Face Recognition System
• Easy to access and install