OVERVIEW of Face Recognition based Door Lock using Raspberry Pi B+ OpenCV
Face recognition is an amazing field of computer vision with many possible applications to hardware and devices. Using embedded SOC platforms like the Raspberry Pi and open source computer vision libraries like OpenCV, you can now add face recognition to your own maker projects! In this project, I’ll show you how to build a face recognition based door lock which unlocks itself using face recognition running on a Raspberry Pi.
For this face recognition based door lock project, you need basic skills related to Linux, Raspberry Pi and electronics. If you are not confident with Raspberry Pi you can take any free tutorial from YouTube.
If you are looking for other IOT projects please check this link >>>>
https://www.arnabkumardas.com/category/topics/iot/
HARDWARE NEEDED
Click on Each Product Below and You will be Taken to the Product Page that I trust and have used in my Project. I Highly Recommend You Buy Directly from the Link Below or Add to Cart.
- Raspberry Pi 3 B+
- SD Card 16GB 98Mbps For Fast Performance
- Raspberry Pi Camera
- Servo Motor
- 10k -ohm 1/4 watt resistor
- Push Button
- Hookup Wires
- 6V Power Supply for Servo
- Wood / Glue and Misc for Construction
PROJECT GUIDE AND TUTORIAL
My Door Lock is based on this below adafruit Tutorial by Toiy DiCola
Please follow his tutorial to learn how this is made. Below is a video of my project’s demonstration.
https://learn.adafruit.com/raspberry-pi-face-recognition-treasure-box/
This implementation of facial recognition involves Principal component analysis (PCA) and Eigenfaces. The Principal Component Analysis (PCA) was independently proposed by Karl Pearson (1901) and Harold Hotelling (1933) to turn a set of possibly correlated variables into a smaller set of uncorrelated variables. The idea is, that a high-dimensional dataset is often described by correlated variables and therefore only a few meaningful dimensions account for most of the information. The PCA method finds the directions with the greatest variance in the data, called principal components.
Here is the documentation for Eigenface and its implementation >>>
https://docs.opencv.org/2.4/modules/contrib/doc/facerec/facerec_tutorial.html#eigenfaces
LINKS
Git >> https://github.com/arnabdasbwn
Follow me on Instagram >> https://www.instagram.com/arnabdasbwn/
Follow me on Twitter >> https://twitter.com/ArnabDasBwn
Subscribe to my YouTube Channel >> https://www.youtube.com/c/ArnabDasBwn
Credits: Adafruit, Tony DiCola
26 Comments
shreeram · May 2, 2019 at 8:17 pm
i am not able to install the opencv dependencies…please help me…i have to make this project
shaggy · May 5, 2019 at 10:44 pm
Hi. when I run the code I always get the attribution error on >> attributeerror: type object ‘rpi.gpio.pwm’ has no attribute ‘servo’ <<
What do I do ??
Crazy Engineer · May 9, 2019 at 6:12 pm
Hi, Try to resolve the Dependencies
Tareq · December 25, 2019 at 11:17 pm
The code in the link is outdated it might only work with pi2
Can you please share your code with me
Thank you
Namrata · November 7, 2020 at 5:25 pm
Hello sir I want this project of face recognition door lock system using Raspberry pi what would be the total cost.Please let me know