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.
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
- Clone this repository
- Change directory to the folder where the file is located
- Run guiPCA.m
- Step use the GUI
- Run program
- Select image that want to recognize using"browse" button
- Click "Recognize" button to recognize face that you chose
- Click "reset" button to reset all of the image and edit text
- Click "exit" button to close the GUI and program
What things you need to install the software and how to install them
- Matlab
- Image Processing Toolbox
Install via Add-Ons Matlab
- Dandi Trianta Barus - Initial work - dandibaroes
This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details