PCA Based Face Recognition System Using ORL Database

This Package implements 'Eigenface' PCA based face recognition technique.

バージョン 1.15 (227 KB)
ダウンロード: 10.2K 件
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2021/10/21

現在この提出コンテンツをフォロー中です。

This package implements a well-known PCA-based face recognition method, which is called 'Eigenface'.
The program is easy to use. Furthermore, a sample Project file demo_PCA.m' is added that demonstrate how to use, ORL training and test database is also included to show Performance comparison for execution time and Recognition percentage, on different size of testing and training dataset by picking images randomly.
Additional file LOOCV.m for LOOCV (Leave One Out Cross Validation) Test.
Additional file Comparision.m for Comparision of PCA with mean,mode and median modifications.
Additional file PRR.m is added in the Sub Functions for calculating Precision and Recall of individual class.
for better understanding of PCA and the Tests involved you can use the tutorials given : http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf
http://www.creighton.edu/fileadmin/user/HSL/docs/ref/Searching_-_Recall_Precision.pdf
ORL Dataset Description and source
Introduced by Ferdinand Samaria et al. in Parameterisation of a stochastic model for human face identification
The ORL Database of Faces contains 400 images from 40 distinct subjects. The size of each image is 92x112 pixels, with 256 grey levels per pixel.Source: https://cam-orl.co.uk/facedatabase.html

引用

Shujaat Khan (2026). PCA Based Face Recognition System Using ORL Database (https://jp.mathworks.com/matlabcentral/fileexchange/43610-pca-based-face-recognition-system-using-orl-database), MATLAB Central File Exchange. に取得済み.

謝辞

ヒントを得たファイル: Kernel PCA and Pre-Image Reconstruction

ヒントを与えたファイル: Radial Basis Function with K Mean Clustering

カテゴリ

Help Center および MATLAB Answers で Dimensionality Reduction and Feature Extraction についてさらに検索

一般的な情報

MATLAB リリースの互換性

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プラットフォームの互換性

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新しいタブで開く
バージョン 公開済み リリース ノート
1.15

Download Dataset from Original Source
1.14

Toolbox for R2014b
1.13.0.0

Additional file PRR.m is added in the Sub Functions for calculating Precision and Recall of individual class.
Recogniton.m and PCA_NEW.m files are slightly modified for the exchange of arguments( variable outd and recd )
1.12.0.0

Additional Comparision file for PCA comparision with [Mean,Mode, and Median]
1.11.0.0

* Bug Fixing in Recognition.m Function
* Addition of Some Comments
1.10.0.0

* Sub_Functions folder
* More detailed Graphs
1.9.0.0

* Additional file LOOCV.m for LOOCV (Leave One Out Cross Validation) Test.
* CDT.m file Upper/Lower case file extension support
* Invalid Dimensions Check in demo_PCA.m

1.8.0.0

* New improved Code with new functions, reduced redundancy in code
* Well Commented with detail explanation
* direct selection of required dimensions
* EigenVectors are normalized
* CDTr and CDTs is replaced with new CDT.m file

1.5.0.0

* Random Selection of training and testing images
* More generic code; support for custom database

1.0.0.0