public void writeFeatureXML()
{
XmlWriterSettings settings = new XmlWriterSettings();
settings.Indent = true;
settings.NewLineChars = "\r\n";
System.Xml.XmlWriter xmlWriter = System.Xml.XmlWriter.Create("C:\\major\\ProjectedPatterns.xml", settings);
xmlWriter.WriteStartDocument();
xmlWriter.WriteStartElement("Pattens");
/*
* for(int u=1;u<=5;u++)
* {
* xmlWriter.WriteElementString("TotalPatterns"+u, Convert.ToString(5));
* }
* xmlWriter.WriteElementString("TotalPatterns11", Convert.ToString(5));
*
* int[] patOfFace = new int[10];
* try
* {
* Bitmap faceToProject = (Bitmap)Image.FromFile("C:\\major\\knownfaces\\1.jpg");
* FaceRecognition.searchDetected_ic(faceToProject);
* int[] patttt = FaceRecognition.getEudPat();
* for (int u = 1; u <= 10; u++)
* {
* xmlWriter.WriteElementString("TotalPatterns" + u, Convert.ToString(patttt[u - 1]));
* }
* }
*
* catch (Exception ex)
* {
* MessageBox.Show(ex.Message);
* }
*/
//--------------------------------Known-----------------------------
string faceFileLocationKnown = "C:\\major\\knownfaces\\";
xmlWriter.WriteStartElement("KnownPatterns");
for (int j = 1; j <= noOfKnownPatterns; j++)
{
string wrtStr = "KnownPattern" + Convert.ToString(j);
xmlWriter.WriteStartElement(wrtStr);
Bitmap faceToProject = (Bitmap)Image.FromFile(faceFileLocationKnown + "k" + j + ".jpg");
//*********This will return first 10 minimum euclidian distances of the face stored in faceToProject****
FaceRecognition.searchDetected_ic(faceToProject);
int[] patOfFace = FaceRecognition.getEudPat();
//*********
//double[,] projectedFeatureRLDA = FaceRecognition.getRLdaFeatures(faceToProject);
//for (int i = 0; i < projectedFeatureRLDA.GetLength(0); i++)
//for (int i = 0; i < netSizeVCT; i++)//netSizeVCT is no of element in each pattern
for (int i = 0; i < netSizeVCT; i++)//netSizeVCT is no of element in each pattern
{
string s3 = "KnownPatternElement" + i;
string feature = Convert.ToString(patOfFace[i]);
xmlWriter.WriteElementString(s3, feature);
}
xmlWriter.WriteEndElement();
}
xmlWriter.WriteEndElement();
//---------------------------------------------------------------------
//--------------------------------Unknown-----------------------------
string faceFileLocationUnknown = "C:\\major\\unknownfaces\\";
xmlWriter.WriteStartElement("UnknownPatterns");
for (int j = 1; j <= noOfUnknownPatterns; j++)
{
string wrtStr = "UnknownPattern" + Convert.ToString(j);
xmlWriter.WriteStartElement(wrtStr);
Bitmap faceToProject = (Bitmap)Image.FromFile(faceFileLocationUnknown + "NiD (" + j + ").jpg");
//*********This will return first 10 minimum euclidian distances of the face stored in faceToProject****
FaceRecognition.searchDetected_ic(faceToProject);
int[] patOfFace = FaceRecognition.getEudPat();
//*********
//double[,] projectedFeatureRLDA = FaceRecognition.getRLdaFeatures(faceToProject);
//for (int i = 0; i < projectedFeatureRLDA.GetLength(0); i++)
for (int i = 0; i < netSizeVCT; i++)
{
string s3 = "UnknownPatternElement" + i;
string feature = Convert.ToString(patOfFace[i]);
xmlWriter.WriteElementString(s3, feature);
}
xmlWriter.WriteEndElement();
}
xmlWriter.WriteEndElement();
//---------------------------------------------------------------------
xmlWriter.WriteEndElement();
xmlWriter.Close();
}
public int recogn(Bitmap imgtrec)
{
int indel = 0;
float tmean = 0; //mean of test image
//float[,] testim;
// final vector of the distance
ImageProcessingUtilities.hist_equalize(imgtrec);
//if (imgtrec.PixelFormat == PixelFormat.Format8bppIndexed)
//{
BitmapData bmData = imgtrec.LockBits(new Rectangle(0, 0, imgtrec.Width, imgtrec.Height), ImageLockMode.ReadWrite, imgtrec.PixelFormat);
unsafe
{
int j = 0;
byte *p = (byte *)(void *)bmData.Scan0.ToPointer();
int stopAddress = (int)p + bmData.Stride * bmData.Height;
//while ((int)p != stopAddress)
while ((int)p != stopAddress)
{
testIm[0, j] = p[0];
j++;
p++;
}
p = null;
j = 0;
}
imgtrec.UnlockBits(bmData);
//}
/////////Deviation from mean////////////////////////
//MessageBox.Show("stemp" + stemp.GetLength(0) + "," + stemp.GetLength(1) + "\n" + testIm.GetLength(0) + "," + testIm.GetLength(1));
for (int i = 0; i < testIm.GetLength(1); i++)
{
tmean = tmean + testIm[0, i];
}
tmean /= testIm.GetLength(1);
//MessageBox.Show(tmean.ToString());
for (int i = 0; i < testIm.GetLength(1); i++)
{
testIm[0, i] = testIm[0, i] - tmean;
}
///////// imgR*V V=stemp///////////////////////
//ThreadStart m1 = new ThreadStart(th1);
//Thread mth1 = new Thread(m1);
//mth1.Start();
//ThreadStart m2 = new ThreadStart(th2);
//Thread mth2 = new Thread(m2);
//mth2.Start();
//ThreadStart m3 = new ThreadStart(th3);
//Thread mth3 = new Thread(m3);
//mth3.Start();
//testim = this.matmul(ref imgR, ref stemp);
float sum1 = 0;
dis_eu = new float[1, trainData / 4];
for (int j = 0; j < (trainData / 4); j++)
{
sum1 = 0;
for (int k = 0; k < testIm.GetLength(1); k++)
{
sum1 += testIm[0, k] * stemp[k, j];
}
dis_eu[0, j] = sum1;
}
//MessageBox.Show("coordinate" + dis_eu[0, 0] + "," + dis_eu[0, 1] + "," + dis_eu[0, 2] + "," + dis_eu[0, 3] + ",");
//this.savp("justy", testim);
/*
* double[,] rett = new double[testim.GetLength(0), testim.GetLength(1)];
* for (int i = 0; i < rett.GetLength(0); i++)
* {
*
* for (int j = 0; j < rett.GetLength(1); j++)
* rett[i, j] = (double)testim[i, j];
*
* }
*/
//MessageBox.Show("rc=(" + rc.GetLength(0) + "," + rc.GetLength(1)+")\n"+trainData);
///////////////recognition//////////////////////////
double devsumsq = 0;
el = new double[1, trainData];
for (int i = 0; i < trainData; i++)
{
for (int j = 0; j < (trainData / 4); j++)
{
devsumsq += Math.Pow((rc[i, j] - dis_eu[0, j]), 2);
}
el[0, i] = Math.Pow(devsumsq, .5);
devsumsq = 0;
}
double min = el[0, 0];
for (int i = 0; i < trainData; i++)
{
if (el[0, i] < min)
{
min = el[0, i];
indel = i;
}
}
minEudDistance = (int)min;
//MessageBox.Show("Index:"+indel.ToString());
int classIndex;
/*
* if (min > 4500)
* {
* indel = -1;
* MessageBox.Show("Unknown Face");
* }
*/
//else
{
classIndex = indel / 10;
indel = 1 + (indel / 10) * 10;
//MessageBox.Show("min : " + Convert.ToString(min));
double maxE = findMaxEuclidian();
//MessageBox.Show("max : " + Convert.ToString(maxE));
//MessageBox.Show("diff : " + Convert.ToString(maxE - min));
}
//this code will set the input vector for lvq
/*
* int inputVectorIndex=1;
* LVQ.setInputVectors(minEudDistance, 0);
* for (int i = indel; i < (indel + 5); i++)
* {
* LVQ.setInputVectors((int)el[0,i], inputVectorIndex);
* inputVectorIndex++;
* }
*/
Sorter.BubbleSort(el);
int[] pat = Sorter.getSortedPatterns();
FaceRecognition.writeEudPat(pat);
return(indel);
}