/// <summary>
/// Function used to get top FaceRecognition.Properties.Settings.Default.DReductionVal Image vectors
/// </summary>
/// <param name="OriginalEigenVector"></param>
/// <param name="EigenVectorForImage"></param>
public void GetTopEigenVectors(PCALib.IMatrix OriginalEigenVector, ref double[][] EigenVectorForImage)
{
for (int iRow = 0; iRow < OriginalEigenVector.Rows; iRow++)
{
for (int iColumn = 0; iColumn < PCA_App.Properties.Settings.Default.DReductionVal; iColumn++)
{
if (iColumn == 0)
{
EigenVectorForImage[iRow] = new double[PCA_App.Properties.Settings.Default.DReductionVal];
}
EigenVectorForImage[iRow][iColumn] = new double();
EigenVectorForImage[iRow][iColumn] = OriginalEigenVector[iRow, iColumn];
}
}
}
void GetImageMatrix()
{
//Code for Intializing Matrix
MainImageMatrix_forAllImages = new double[1][];
double[][] MainImageMatrix_Covariance = new double[1][];
CopyImageMatrix_forallImages = new double[1][];
//InitializeMatrix_1(ref MainImageMatrix);
// Call function to fetch all image in a matrix format
//Get data image from "Data" folder to an array (first dimension is pixel value, second dimension is image index)
_objMatrix.InitializeMatrix(ref MainImageMatrix_forAllImages);
// just copy from "MainImageMatrix_forAllImages" to "CopyImageMatrix_forallImages"
_objMatrix.CopyMatrix(MainImageMatrix_forAllImages, ref CopyImageMatrix_forallImages);
//Code for finding means vector from the MainImage Matrix
MeanVector = new double[1][];
// calculate the mean value of pixel value for each image
MeanVector = _objMatrix.GetMeanVector(ref MainImageMatrix_forAllImages);
//Performing Step 2 of Algorithm
_objMatrix.getMeanAdjustedMatrix(ref MainImageMatrix_forAllImages, MeanVector);
//Compute Covariance matrix
MainImageMatrix_Covariance = _objMatrix.getCovarianceMatrix(MainImageMatrix_forAllImages);
//Computing Eigen values and Eigen vecotors by suding MaPack library
PCALib.Matrix obj = new Matrix(MainImageMatrix_Covariance);
IEigenvalueDecomposition EigenVal;
EigenVal = obj.GetEigenvalueDecomposition();
// Take only top 10 eigen values
double[] EigenValforImage = new double[PCA_App.Properties.Settings.Default.DReductionVal];
double[][] TransposevalImage = new double[PCA_App.Properties.Settings.Default.DReductionVal][];
EigenFaceImage = new double[PCA_App.Properties.Settings.Default.DReductionVal][];
EigenVectorforImage = new double[PCA_App.Properties.Settings.Default.DefaultNumberOfImages][];
// double[][] PixelmatrixforImage = new double[FaceRecognition.Properties.Settings.Default.DefaultNumberOfImages][];
_objMatrix.GetTopEigenValues(EigenVal.RealEigenvalues, ref EigenValforImage);
// Taking top 10 Eigen vectors
PCALib.IMatrix EigenVector = EigenVal.EigenvectorMatrix;
_objMatrix.GetTopEigenVectors(EigenVector, ref EigenVectorforImage);
// _objMatrix.Transpose(CopyImageMatrix, ref TransposevalImage);
_objMatrix.Multiply(MainImageMatrix_forAllImages, EigenVectorforImage, ref EigenFaceImage);
// Transpose the Eigen Face images so that we can use inbuilt max and min function in array.
_objMatrix.Transpose(EigenFaceImage, ref TransposevalImage, PCA_App.Properties.Settings.Default.DReductionVal);
double[][] PixelmatrixforImage = new double[PCA_App.Properties.Settings.Default.DReductionVal][];
_objMatrix.ConvertinPixelScale(TransposevalImage, ref PixelmatrixforImage, EigenFaceImage.Length);
// _objMatrix.Transpose(PixelmatrixforImage, ref TransposevalImage,EigenFaceImage.Length);
//int iControl = 0;
/* foreach (Control cobj in gbxImages.Controls)
* {
* if (cobj is PictureBox)
* {
* cobj.BackgroundImage = _objMatrix.DrawFaceValue(PixelmatrixforImage, iControl);
* iControl++;
* }
*
* }*/
BaseMatrix = new double[clsMatrixOperation.iDefaultImageCount][];
double[][] ProductMatrix = null;
double[][] Transponse_EachImage = new double[PCA_App.Properties.Settings.Default.DReductionVal][];
for (int irow = 0; irow < clsMatrixOperation.iDefaultImageCount; irow++)
{
Transponse_EachImage = new double[EigenFaceImage.Length][];
_objMatrix.Transpose(MainImageMatrix_forAllImages, ref Transponse_EachImage, 1, irow + 1);
_objMatrix.Multiply(Transponse_EachImage, EigenFaceImage, ref ProductMatrix);
for (int iColumn = 0; iColumn < clsMatrixOperation.iDimensionalReduction; iColumn++)
{
if (iColumn == 0)
{
BaseMatrix[irow] = new double[clsMatrixOperation.iDimensionalReduction];
}
BaseMatrix[irow][iColumn] = new double();
BaseMatrix[irow][iColumn] = ProductMatrix[0][iColumn];
}
}
// _objMatrix.Multiply(CopyImageMatrix, EigenFaceImage, ref BaseMatrix);
}
