Face Recognition Project

The project is divided into 4 modules

The project is built for educational purposes, to learn how to apply feature engineering techniques, so it may be slower or have a lower accuracy than the library functions, but the accuracy is acceptable

1. Face Detection

2. Landmark Detection

3. Recognition using Eigen Faces

4. Recognition using Local Binary Pattern Histograms

A demo video for the module: https://youtu.be/9adhzAfto0I

Applying Local Binary Patterns filter to get a LBP image after using the preprocessed grayscale version of the image, applying a histogram comparison to get the closeness of any two images to check the identity of the person