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PCA-based Face Recognition System

PCA-based Face Recognition System


Amir Omidvarnia (view profile)


20 Oct 2007 (Updated )

This package implements 'Eigenface', a PCA-based face recognition system.

function T = CreateDatabase(TrainDatabasePath)
% Align a set of face images (the training set T1, T2, ... , TM )
% Description: This function reshapes all 2D images of the training database
% into 1D column vectors. Then, it puts these 1D column vectors in a row to 
% construct 2D matrix 'T'.
% Argument:     TrainDatabasePath      - Path of the training database
% Returns:      T                      - A 2D matrix, containing all 1D image vectors.
%                                        Suppose all P images in the training database 
%                                        have the same size of MxN. So the length of 1D 
%                                        column vectors is MN and 'T' will be a MNxP 2D matrix.

% Original version by Amir Hossein Omidvarnia, October 2007
%                     Email:                  

%%%%%%%%%%%%%%%%%%%%%%%% File management
TrainFiles = dir(TrainDatabasePath);
Train_Number = 0;

for i = 1:size(TrainFiles,1)
    if not(strcmp(TrainFiles(i).name,'.')|strcmp(TrainFiles(i).name,'..')|strcmp(TrainFiles(i).name,'Thumbs.db'))
        Train_Number = Train_Number + 1; % Number of all images in the training database

%%%%%%%%%%%%%%%%%%%%%%%% Construction of 2D matrix from 1D image vectors
T = [];
for i = 1 : Train_Number
    % I have chosen the name of each image in databases as a corresponding
    % number. However, it is not mandatory!
    str = int2str(i);
    str = strcat('\',str,'.jpg');
    str = strcat(TrainDatabasePath,str);
    img = imread(str);
    img = rgb2gray(img);
    [irow icol] = size(img);
    temp = reshape(img',irow*icol,1);   % Reshaping 2D images into 1D image vectors
    T = [T temp]; % 'T' grows after each turn                    

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