Face-Recognition-Using-PCA-and-Euclidean-Classifier

In this repo, I will using Principal Component Analysis and Euclidean Classifier for face recognition with GUI. Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. To clasify the image, I use euclidean classifier. The Euclidean classifier is also known as the Euclidean distance classifier. This classifier is used to measure the distance between a set of samples in the N-dimensional feature space.

Demo

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

• To use this demo

1. Clone this repository
2. Change directory to the folder where the file is located
3. Run guiPCA.m

• Step use the GUI

1. Run program
2. Select image that want to recognize using"browse" button
3. Click "Recognize" button to recognize face that you chose
4. Click "reset" button to reset all of the image and edit text
5. Click "exit" button to close the GUI and program

Prerequisites

What things you need to install the software and how to install them

1. Matlab

Install Matlab

2. Image Processing Toolbox

Install via Add-Ons Matlab

Authors

• Dandi Trianta Barus - Initial work - dandibaroes

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details