Overview

LBPH -> Local Binary Patterns Histogram

It is based on local binary operator. It is widely used in facial recognition due to its computational simplicity and discriminative power.

It is very efficient texture operator which labels the pixels of an image by thresholding the neighborhood of each pixel and considers the result as a binary number. The steps involved to achieve this are:

• creating dataset
• face acquisition
• feature extraction
• classification

The LBPH algorithm is a part of opencv.

Dependencies

pip install numpy
pip install opencv-python
pip install opencv-contrib-python

Quick-Start

• Fork the repository

click on the uppermost button

1. Create virtual environment

python -m venv env

2. Linux

source env/bin/activate

OR

2. Windows

env\Scripts\activate

• Clone the repository using-

git clone https://github.com/akshitagupta15june/LBPH-Face-Recognition.git

• Install Dependencies

• Execute -

face images samples collection

  python recognition-part-1.py 

model training + final recognition

  python recognition-part-2.py 

Note: Make sure you have haarcascade_frontalface_default.xml file