/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
///
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
///
public object Clone()
{
var clone = new LocalBinaryPattern(blockSize, cellSize, normalize);
clone.epsilon = epsilon;
return(clone);
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
///
protected override object Clone(ISet <PixelFormat> supportedFormats)
{
var clone = new LocalBinaryPattern(blockSize, cellSize, normalize);
clone.epsilon = epsilon;
clone.SupportedFormats = supportedFormats;
return(clone);
}
/// <summary>
/// Creates a new object that is a copy of the current instance.
/// </summary>
///
/// <returns>
/// A new object that is a copy of this instance.
/// </returns>
///
public object Clone()
{
var clone = new LocalBinaryPattern(blockSize, cellSize, normalize);
clone.epsilon = epsilon;
clone.histograms = (int[, ][])histograms.Clone();
clone.patterns = (int[, ])patterns.Clone();
return(clone);
}
public void Feature_extraction()
{
Image <Bgr, byte> inputimage = new Image <Bgr, byte>(@"C:\Users\temp\Desktop\facebitmap.jpg");
FileStream fs = new FileStream(@"C:\Users\temp\Desktop\Face_feature.txt", FileMode.Create, FileAccess.Write);
StreamWriter sw = new StreamWriter(fs);
LocalBinaryPattern lbp = new Accord.Imaging.LocalBinaryPattern(3, 6, true);
Image <Gray, byte> gray = inputimage.Convert <Gray, byte>();
// Image<Gray, byte> newgray = Resizegray(gray);
// newgray._EqualizeHist();
// Image<Gray, byte> mask = new Image<Gray, byte>(newgray.Width, newgray.Height);
// Image<Gray, byte> dest = new Image<Gray, byte>(newgray.Width, newgray.Height);
// CvInvoke.cvEllipse(mask, new Point(55, 50), new Size(52, 80), 0, 0, 360, new MCvScalar(256, 256, 256), -1, Emgu.CV.CvEnum.LINE_TYPE.CV_AA, 0);
// dest = newgray.And(newgray, mask);
// var newdest = dest.GetSubRect(new Rectangle(new Point(20, 23), new Size(80, 84)));
//newdest.SmoothBilatral(0, 20, 2);
// lbp.ProcessImage(newdest.Bitmap);
for (int i = 0; i < 13; i++)
{
for (int j = 0; j < 14; j++)
{
pixel1.Add(lbp.Histograms[i, j]);
}
}
// Matrix<float> pixeldata = new Matrix<float>(256, 256);
for (int j = 0; j < 13 * 14; j++)
{
var pixe = pixel1[j];
for (int i = 0; i < 256; i++)
{
// lbpdata[0, i] += pixe[i];
Finaldata.Add(pixe[i]);
}
}
// CvInvoke.cvNormalize(pixeldata, pixeldata, 1, -1, NORM_TYPE.CV_L2, empty);
string str = " ";
sw.Write((4) + " ");
for (int j = 0; j < 182 * 256; j++)
{
sw.Write((j + 1) + ":" + Finaldata[j] + str);
sw.Write("");
}
sw.WriteLine();
sw.Close();
pixel1.Clear();
Finaldata.Clear();
/*
* for (int o = 0; o <64*256; o++)
* {
* SVMNode node = new SVMNode();
* node.Index = Convert.ToInt32(o);
* node.Value = Convert.ToDouble(Finaldata[o]);
* nodes.Add(node);
* }
* problem.Add(nodes.ToArray(), 1);
* pixel1.Clear();
* Finaldata.Clear();
* return problem;
*/
}
