Dear Readers: Welcome to The Engineering Projects

## Sunday, 1 May 2011

### Face Access - High Level Design

Page Views:

Our design is split into three different processes: training, enrolling, and logging in.

#### Training

The training process is the only time we use a computer; once this step is complete, the system is completely standalone. If we were to sell this system as a consumer product, we would ship the system pre-trained. The training process consists of teaching the system to key in on the most important features of a face. To do this, a large number of facial images are taken and sent to Matlab to help the system determine the distinguishing features of a face. We use Matlab to create the eigenfaces, which are the principle components of the training set (See Principal Component Analysis). Because the images were too large to be held on the microcontroller, we captured an image a line at a time, sending each line to flash before the camera sends the next line. We then send the image through the microcontroller to Matlab over the serial port. Once all of the training images are in Matlab the eigenfaces and average face are created (see Background Math for more information). Finally, the eigenfaces and average face are sent to flash memory through the microcontroller. Once the eigenfaces and average face are in flash, the system is completely standalone.

#### Enrolling

Before a user can login to the system, he first needs to register his face and enroll it into the database. To enroll into the system, the user presses the enroll button, which will capture the image. Before the image is captured, the current number of system users is checked; if the maximum number of users is met the new user cannot be enrolled. We set our maximum to 20 users. If the maximum hasn't been met, the user's face image is captured and is once again sent to flash memory 176 bytes at a time (same as in the training process) and is stored there temporarily for calculation. The image and eigenfaces are all pulled back to the microcontroller 528 bytes at a time to calculate the new user's "template", which is a short vector describing the user's correlation with the eigenfaces. (see Background Math for more information). The template is then compared with the previously stored templates; if the new template is too close to a previous template, the user cannot be enrolled. We defined the "closeness" between two templates as the cosine of the angle between them. If there are no matches, the new template is added to the database in flash memory to save it in case of a system reset.

#### Logging in

The Logging In process is initially very similar to enrolling. The user presses the login button to take his picture, store it in flash memory and begin the logging in process. Again the newly captured image and eigenfaces are pulled from flash back to the micrcontroller 528 bytes at a time to calculate the user's template. This template is compared with all of the previous templates. For the user to be logged in, their template needs to "match" (be close enough to) only one saved template; otherwise they will be "denied access". Again, the cosine of the angle between the two templates is used to determine template match. Whether or not the user was logged in, the top three matches are displayed on the LCD.

#### Erasing Users

We currently only have the system setup to have up to 20 enrolled users. However, for demo purposes we wanted the ability to enroll new users and erase the old ones. To do this we added a final button on the back of our protoboard for this purpose. The button needs to be held down for an entire second before the function to erase templates is called. A message is displayed to the LCD to let the user know that the enrollments have been erased.

#### Standards Used

For communicating with flash memory we used the Serial Peripheral Interface (SPI). For programming the camera we used the Inter-Integrated Circuit (I2C) interface. The video signal was digital, so it was not NTSC, but understanding the NTSC standard helped us understand the camera output.

#### Intellectual Property

The eigenface method is in the literature, so we have no intellectual property concerns. We plan to try to publish our results, so we are fully disclosing our design.

If you don't want to get yourself into Serious Technical Trouble while doing your programming OR technical projects then just sit back and relax and let us do the Job for you at a fairly reasonable cost. Submit your project details by Clicking Here »

I am Syed Zain Nasir, the founder of The Engineering Projects (TEP). I am a programmer since 2009 before that I just search things, make small projects and now I am sharing my knowledge through this platform.I also work as a freelancer and did many projects related to programming and electrical circuitry.

 Follow @theenggprojects In 61 people's circles

# Subscribe To Get FREE Tutorials!

#### Confused? Feel free to ask

Your feedback is always appreciated. I will try to reply to your queries as soon as time allows.
Note:-
Please do not spam Spam comments will be deleted immediately upon my review.

Regards,