Face Verification System

Quick Overview and Description

This project demonstrates a face verification system that compares a face extracted from an ID card with a face captured from a selfie. The system uses OpenCV for image processing, Dlib for face detection, and the face_recognition library for face encoding and comparison. The primary use case is to verify if the person in the selfie matches the person in the ID card photo.

Built With

• OpenCV: For image processing and manipulation.
• Dlib: For face detection.
• face_recognition: For face encoding and comparison.
• Google Colab: For providing the computing environment.

How to Use

Prerequisites

Make sure you have the necessary libraries installed. You can use Google Colab to avoid installation issues and leverage GPU acceleration.

Steps

1. Set Up Environment:

   • Open the provided Google Colab link.
   • Switch to GPU acceleration by going to Runtime -> Change runtime type -> Hardware accelerator -> GPU.

2. Install Dependencies:

   • Run the cells to install necessary libraries (opencv-python, dlib, and face_recognition).

3. Upload Your Images:

   • Use the upload cell to upload the ID card image and selfie image.

4. Extract Frontal Photos:

   • Run the provided function to extract the frontal photo from the uploaded ID card and selfie images.

5. Compare Faces:

   • Run the provided function to compare the extracted faces and determine if they match.

Link to Google Colab

You can find the Google Colab notebook here: Google Colab Link

Built By

Firas Al Kharusi firas@firasb.com