Beagle Board - beagleboard.org
Eshtaartha BasuCathy Wicks
Published © MIT

Biometric Door Opener with Facial Recognition & Voice Output

Quickly automate any door with facial recognition, motion detection, motor control & text to speech using BeagleBone Black Wireless.

AdvancedFull instructions provided7 hours1,450

Things used in this project

Hardware components

BeagleBone Black Wireless
BeagleBoard.org BeagleBone Black Wireless
×1
MikroElektronika Motion Click MIKROE-1589
×1
Mouser Motor Driver Module from OSEPP
×1
Webcam - Logitech HD C920
×1
Geared DC Motor 118RPM @ 12V
×1
12-VOLT DC 3000MA POWER ADAPTER by Rhino
×1
Metal Wire Rope - 1/8in Galvanized, uncoated
×1
Actobotics Aluminum Channel
×1
USB-SBCV USB 2.0 Sound Card - Sabrent
×1
Wireless Portable Speaker with rechargeable battery
×1
Actobotics 6mm Bore Screw Hub
×1
Powered USB Hub
×1

Story

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Code

Automated Door Lock with Facial Recognition and Voice Output

Python
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Automated Door Lock with Facial Recognition and Voice Output on BeagleBone Black Wireless (powered by OSD335x)
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License: Copyright 2018, Octavo Systems, LLC. All rights reserved.

The Software is available for download and use subject to the terms and
conditions of this License. Access or use of the Software constitutes
acceptance and agreement to the terms and conditions of this License.

Redistribution and use of the Software in source and binary forms, with
or without modification, are permitted provided that the following conditions
are met:
- Redistributions of source code must retain the above copyright notice,
this list of conditions and the capitalized paragraph below.
- Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the capitalized paragraph below in the
documentation and/or other materials provided with the distribution.

The names of the software's authors or their organizations may not be used
to endorse or promote products derived from the Software without specific
prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
THE POSSIBILITY OF SUCH DAMAGE.

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Overview:

The objective of this project is to automate any office/home door(preinstalled with door closer).
The project uses OpenCV Fisher Face Recognizer to recognize the face of people who are trying to enter the room.
A geared DC Motor is used to actually open the door. A motion click is used to detect indoor motion and open the
door for anyone trying to leave the room. "Flite" voice synthesizer is used to output suitable greeting messages.


Procedure to build OpenCV and run the project code on BeagleBone Black Wireless:

1. Get the latest Debian image from https://beagleboard.org/latest-images

2. Burn the image to an SD card (minimum 8GB required for this project) using the instructions from:
https://beagleboard.org/getting-started#update

3. Expand the File System of your SD card from 4GB to 8GB using the instructions from (See Note below):
http://dev.iachieved.it/iachievedit/expanding-your-beaglebone-microsd-filesystem/

NOTE: In step 6, set the First Sector to 8192 instead of leaving it blank

4. Copy the given files (installScript.sh, getTrainingData.py, trainAndPredict.py,haarcascade_frontalface_default.xml) to the
same directory on your BeagleBone Black Wireless.

5. Make the install script executable:

```sudo chmod +x installScript.sh```

6. Run installScript.sh

The script will install all the necessary dependencies and download OpenCV 3.1.0.

A few issues were found during the build process of OpenCV. Hence, the last 7 lines of this script (installScript.sh) were
intentionally commented to prevent the build process of OpenCV. To avoid possible issues during build, apply the following
fixes:

a. To resolve hdf5.h error:

Open common.cmake:

```nano opencv-3.1.0/modules/python/common.cmake```

Copy and paste the following lines at the end of common.cmake:

```
find_package(HDF5)
include_directories(${HDF5_INCLUDE_DIRS})
```

Save and close the file.

b. OpenCV "predict confidence" wrapper workaround:

Navigate to line 259 of face.hpp

```nano opencv_contrib/modules/face/include/opencv2/face.hpp```

Replace the line with:

```int predict(InputArray src) const;```

Save and close the file.

7. Uncomment the last 7 lines of installScript.sh and rerun the script. The OpenCV build process may take 6 to 10 hours to
complete.


8. The face recognizer needs atleast 2 sets of pictures to train on. Run getTrainingData.py:

```python getTrainingData.py <name of the person in front of the camera>```

Example:

```python getTrainingData.py John```

Once the script starts running, the camera will turn on and you will be able to see "Camera on" message on the console.
Stand right in front of the camera. Once a face is captured, "Face captured" message is displayed on console. A count of
number of pictures captured is also displayed. Atleast 100 pictures per person is necessary to get good predicton.


9. At this point, the Face Recognizer should be ready to Train on the available images and then make Predictions. Run
trainAndPredict.py:

```python trainAndPredict.py```

The script will display messages on the console as it goes through different phases of training.

10. Once "Face Recognition in progress" message is displayed on terminal, the Face Recognizer will be able to predict the name
of the people standing in front of the camera.
No preview (download only).

Automated Door Lock with Facial Recognition and Voice Output

Python
No preview (download only).

Credits

Eshtaartha Basu

Eshtaartha Basu

7 projects • 4 followers
Electrical Engineer by profession but love physics in general. I like to build stuff. Have been building electro-mechanical systems from 15y
Contact
Cathy Wicks

Cathy Wicks

10 projects • 4 followers
Beagleboard.org fan
Contact
Thanks to OpenCV.

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