/// 静态函数
///
private static List <PointF> ComputeDefaultROIPoints(ushort[,] imgData)
{
ushort[,] imagedataTemp = (ushort[, ])imgData.Clone();
int[] rdata = LunImage.FindMaxAndMin(imagedataTemp);
int maxValue = rdata[0];
int minValue = rdata[1];
int lenValue = maxValue - minValue + 1;
int[] histogramData = new int[lenValue];
foreach (int da in imgData)
{
histogramData[da - minValue]++;
}
double sum = 0;
double csum = 0.0;
int n = 0;
int thresholdValue = 0;
for (int k = 0; k < lenValue; k++)
{
sum += (double)k * (double)histogramData[k]; /* x*f(x) 质量矩*/
n += histogramData[k]; /* f(x) 质量 */
}
if (n <= 0)
{
// if n has no value, there is problems...
return(new List <PointF>());
}
// do the otsu global thresholding method
double fmax = -1.0;
int n1 = 0;
int n2 = 0;
double m1, m2 = 0;
for (int k = 0; k < lenValue; k++)
{
n1 += histogramData[k];
if (n1 <= 0)
{
continue;
}
n2 = n - n1;
if (n2 == 0)
{
break;
}
csum += (double)k * histogramData[k];
m1 = csum / n1;
m2 = (sum - csum) / n2;
double sb = (double)n1 * (double)n2 * (m1 - m2) * (m1 - m2);
/* bbg: note: can be optimized. */
if (sb > fmax)
{
fmax = sb;
thresholdValue = k;
}
}
for (int i = 0; i < imagedataTemp.GetLength(0); i++)
{
for (int j = 0; j < imagedataTemp.GetLength(1); j++)
{
if (imagedataTemp[i, j] < thresholdValue)
{
imagedataTemp[i, j] = 0;
}
else
{
imagedataTemp[i, j] = (ushort)thresholdValue;
}
}
}
int level = thresholdValue / 2;
int window = thresholdValue / 5;
Histogram his = new Histogram(imagedataTemp);
int HFMax = level + window / 2;
int HFMin = level - window / 2;
if (HFMax < 0 || HFMin < 0)
{
level = his.WinCenter;
window = his.WinWidth;
}
else
{
if (HFMax > his.MaxValue || HFMin > his.MaxValue)
{
level = his.WinCenter;
window = his.WinWidth;
}
}
int maxvalue = his.LenValue < 256 ? 256 : his.LenValue;
maxValue = maxvalue;
minValue = his.MinValue;
Color[] LUT = HisLUT.RefreshLUT(null, false, level, window, maxvalue, minValue);
Bitmap BMP = TypeConvert.SliceImageToBitmap24(imagedataTemp, LUT, minValue);
float x1 = 0;
float y1 = 0;
float x2 = BMP.Width - 1;
float y2 = BMP.Height - 1;
BoundaryTracker bt = new BoundaryTracker();
bt.GetSerializedBoundary(BMP, LUT[0], new Rectangle((int)x1, (int)y1, (int)(x2 - x1 + 1), (int)(y2 - y1 + 1)), false);
List <PointF> temp = new List <PointF>();
if (bt.MaxPointIdx != -1)
{
PointF[] tmp = bt.CL[bt.MaxPointIdx];
if (tmp.Length > 3)
{
for (int i = 0; i < tmp.Length; i++)
{
temp.Add(tmp[i]);
}
}
}
else
{
temp.Add(new PointF(0, 0));
temp.Add(new PointF(0, BMP.Height - 1));
temp.Add(new PointF(BMP.Width - 1, BMP.Height - 1));
temp.Add(new PointF(BMP.Width - 1, 0));
}
return(temp);
}
private void ComputeDefaultROIPoints()
{
AverageImageObjectBase cbTemp = Clone();
ushort[,] imagedataTemp = cbTemp.imageData;
int[] rdata = LunImage.FindMaxAndMin(imagedataTemp);
int maxValue = rdata[0];
int minValue = rdata[1];
int lenValue = maxValue - minValue + 1;
int[] histogramData = new int[lenValue];
foreach (int da in cbTemp.ImageData)
{
histogramData[da - minValue]++;
}
double sum = 0;
double csum = 0.0;
int n = 0;
int thresholdValue = 0;
for (int k = 0; k < lenValue; k++)
{
sum += (double)k * (double)histogramData[k]; /* x*f(x) 质量矩*/
n += histogramData[k]; /* f(x) 质量 */
}
if (n <= 0)
{
// if n has no value, there is problems...
return;
}
// do the otsu global thresholding method
double fmax = -1.0;
int n1 = 0;
int n2 = 0;
double m1, m2 = 0;
for (int k = 0; k < lenValue; k++)
{
n1 += histogramData[k];
if (n1 <= 0)
{
continue;
}
n2 = n - n1;
if (n2 == 0)
{
break;
}
csum += (double)k * histogramData[k];
m1 = csum / n1;
m2 = (sum - csum) / n2;
double sb = (double)n1 * (double)n2 * (m1 - m2) * (m1 - m2);
/* bbg: note: can be optimized. */
if (sb > fmax)
{
fmax = sb;
thresholdValue = k;
}
}
for (int i = 0; i < imagedataTemp.GetLength(0); i++)
{
for (int j = 0; j < imagedataTemp.GetLength(1); j++)
{
if (imagedataTemp[i, j] < thresholdValue)
{
imagedataTemp[i, j] = 0;
}
else
{
imagedataTemp[i, j] = (ushort)thresholdValue;
}
}
}
cbTemp.SetLUT(null);
cbTemp.level = thresholdValue / 2;
cbTemp.window = thresholdValue / 5;
cbTemp.ImageData = imagedataTemp;
float x1 = 0;
float y1 = 0;
float x2 = BMP.Width - 1;
float y2 = BMP.Height - 1;
BoundaryTracker bt = new BoundaryTracker();
bt.GetSerializedBoundary(cbTemp.BMP, LUT[0], new Rectangle((int)x1, (int)y1, (int)(x2 - x1 + 1), (int)(y2 - y1 + 1)), false);
List <PointF> temp = new List <PointF>();
if (bt.MaxPointIdx != -1)
{
PointF[] tmp = bt.CL[bt.MaxPointIdx];
if (tmp.Length > 3)
{
for (int i = 0; i < tmp.Length; i++)
{
temp.Add(tmp[i]);
}
}
}
else
{
temp.Add(new PointF(0, 0));
temp.Add(new PointF(0, cbTemp.BMP.Height - 1));
temp.Add(new PointF(cbTemp.BMP.Width - 1, cbTemp.BMP.Height - 1));
temp.Add(new PointF(cbTemp.BMP.Width - 1, 0));
}
for (int i = 0; i < temp.Count; i++)
{
float x = ((float)temp[i].X * (float)pixelSize);
float y = ((float)temp[i].Y * (float)pixelSize);
temp[i] = (new PointF(x, y));
}
ROIPoints = temp;
//ImageObjectBase tempcb = cb.Clone();
//RefreshROI(ref tempcb, Color.Red);
//cb.showROI = true;
//cb.BMP = tempcb.BMP;
//loadImagebyJacbi(pictureBox1, cb.BMP, 1);
}
//对所给定的图像进行边缘检测，如果对比度较大，则计算出相应外轮廓
//在ImageROI中添加相应的边界点数组，并添加相应的矩形区域选框
//检测
public void GetBoundaryOfData()
{
ushort[,] data = img.ImageData;
int width = data.GetLength(0);
int height = data.GetLength(1);
int sum = 0;
for (int i = width / 2 - 5; i < width / 2 + 5; i++)
{
for (int j = height / 2 - 5; j < height / 2 + 5; j++)
{
sum += data[i, j];
}
}
int average = sum / 100;
double scale = 0.5;
try
{
scale = double.Parse(CapturePub.readCaptrueValue("EvaluateScaleThreshold"));
}
catch (System.Exception ex)
{
scale = 0.5;
}
int threshold = (int)(average * scale);
Bitmap bmp = (Bitmap)(img.BMP.Clone());
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
if (data[i, j] > threshold)
{
bmp.SetPixel(j, i, Color.Red);
}
}
}
BoundaryTracker bt = new BoundaryTracker();
if (bt.GetSerializedBoundary(bmp, Color.Red))
{
int indexPts = 0;
for (int i = 0; i < bt.CL.Count; i++)
{
if (bt.CL[i].Length > bt.CL[indexPts].Length)
{
indexPts = i;
}
}
if (bt.CL.Count != 0)
{
PointF[] pts = bt.CL[indexPts];
int Xmin = int.MaxValue;
int Xmax = int.MinValue;
int Ymin = int.MaxValue;
int Ymax = int.MinValue;
for (int i = 0; i < pts.Length; i++)
{
if (Xmin > pts[i].X)
{
Xmin = (int)pts[i].X;
}
if (Ymin > pts[i].Y)
{
Ymin = (int)pts[i].Y;
}
if (Xmax < pts[i].X)
{
Xmax = (int)pts[i].X;
}
if (Ymax < pts[i].Y)
{
Ymax = (int)pts[i].Y;
}
}
Point pt1 = new Point(Xmin, Ymin);
Point pt2 = new Point(Xmax, Ymin);
Point pt3 = new Point(Xmax, Ymax);
Point pt4 = new Point(Xmin, Ymax);
Rectangle rect = new Rectangle(pt1, new Size(Xmax - Xmin, Ymax - Ymin));
img.boundaryPoint = new List <Point>()
{
pt1, pt2, pt3, pt4
};
img.BoundaryRect = rect;
img.ROIRectangle = rect;
return;
}
}
img.boundaryPoint = new List <Point>()
{
new Point(0, 0), new Point(data.GetLength(0), 0),
new Point(data.GetLength(0), data.GetLength(1)), new Point(0, data.GetLength(1))
};
img.BoundaryRect = new Rectangle(new Point(0, 0), new Size(data.GetLength(0), data.GetLength(1)));
img.ROIRectangle = img.BoundaryRect;
return;
}
