public static Bitmap MorphologySimpleBinarization(this Bitmap image, int morphologyKernel, byte morphologyThreshold)
{
if (image.PixelFormat != PixelFormat.Format8bppIndexed)
{
throw new NotSupportedException("Filter can be applied to binary 8bpp images only");
}
Erosion morphologyErosion = new Erosion();
Bitmap tempMorphologyImage = morphologyErosion.Apply(image);
for (int i = 0; i < morphologyKernel - 1; i++)
{
tempMorphologyImage = morphologyErosion.Apply(tempMorphologyImage);
}
SimpleGrayImage morphologyImage = new SimpleGrayImage(tempMorphologyImage);
OtsuThreshold thresholdFilter = new OtsuThreshold();
SimpleGrayImage otcuImage = new SimpleGrayImage(thresholdFilter.Apply(image));
for (int i = 0; i < morphologyImage.Cols; i++)
{
for (int j = 0; j < morphologyImage.Rows; j++)
{
if (morphologyImage.Data[j, i] > morphologyThreshold)
{
morphologyImage.Data[j, i] = 255;
}
else
{
morphologyImage.Data[j, i] = otcuImage.Data[j, i];
}
}
}
return(morphologyImage.Bitmap);
}
public KuwaharaPixelProcessing(int x, int y, SimpleGrayImage image, int kernelSize = 2)
{
_x = x;
_y = y;
_image = image;
_kernel = kernelSize;
}
public KuwaharaRegion(Point centerPoint, Point regionPoint, SimpleGrayImage image)
{
_minX = Math.Min(centerPoint.X, regionPoint.X);
_maxX = Math.Max(centerPoint.X, regionPoint.X);
_minY = Math.Min(centerPoint.Y, regionPoint.Y);
_maxY = Math.Max(centerPoint.Y, regionPoint.Y);
_image = image;
_numberOfElements = (_maxX - _minX + 1) * (_maxY - _minY + 1);
}
public LgbtRegion(Point centerPoint, int radius, SimpleGrayImage image)
{
_image = image;
//_image = new SimpleGrayImage(image.Mat);
_minX = Math.Max(centerPoint.X - radius, 0);
_maxX = Math.Min(centerPoint.X + radius, _image.Cols - 1);
_minY = Math.Max(centerPoint.Y - radius, 0);
_maxY = Math.Min(centerPoint.Y + radius, _image.Rows - 1);
_numberOfElements = (_maxX - _minX + 1) * (_maxY - _minY + 1);
}
public LgbtPixelProcessing(int y, int x, SimpleGrayImage image, double k, int localRadius, int globalRadius, byte globalThreshold)
{
_x = x;
_y = y;
_k = k;
_image = image;
//_image = new SimpleGrayImage(image.Mat);
_localRadius = localRadius;
_globalRadius = globalRadius;
_globalThreshold = globalThreshold;
}
public Image Step12DrawBadLines(ref VerificationStatus result, int badLinesLimit)
{
if (!_debugMode)
{
throw new Exception("Can`t use this method in production mode");
}
List <int> badLines = _workingUltrasoundModM.DeviationStreakLines;
SimpleGrayImage rez = new SimpleGrayImage(_workingUltrasoundModM.Image.Data);
badLines.ForEach(line => rez.DrawHorisontalGrayLine(0, _workingUltrasoundModM.Image.Cols - 1, line, 0));
_ultrasoundModeMStatus = badLines.Count < badLinesLimit ? VerificationStatus.Correct : VerificationStatus.Incorrect;
result = _ultrasoundModeMStatus;
return(rez.Bitmap);
}
public UltrasoundModM(double deviationThreshold, int deviationStreakSize, SimpleGrayImage image, int topIndention, int bottomIndention)
{
Image = image;
_topLine = topIndention;
_bottomLine = image.Rows - bottomIndention;
_deviationStreakLines = new List <int>();
_deviations = new double[image.Rows];
_expectations = new double[image.Rows];
_deviationStreakSize = deviationStreakSize;
_deviationThreshold = deviationThreshold;
_iqr = new int[Image.Rows];
SetExpectations();
SetDeviations();
SetIqr();
}
public Image Step15DrawBrightLines(ref VerificationStatus result, int threshold, int brightPixelLimit, int brightLinesLimit)
{
if (!_debugMode)
{
throw new Exception("Can`t use this method in production mode");
}
List <int> briteLines = _workingUltrasoundModM.getBrightLines(threshold, brightPixelLimit);
SimpleGrayImage rez = new SimpleGrayImage(_workingUltrasoundModM.Image.Data);
briteLines.ForEach(line => rez.DrawHorisontalGrayLine(0, _workingUltrasoundModM.Image.Cols - 1, line, 0));
_ultrasoundModeMStatus = briteLines.Count < brightLinesLimit ? VerificationStatus.Correct : VerificationStatus.Incorrect;
result = _ultrasoundModeMStatus;
return(rez.Bitmap);
}
public SimpleGrayImage Apply(SimpleGrayImage image)
{
SimpleGrayImage source = image;
var syncTask = new Task(() =>
{
Parallel.For(0, image.Rows, columnCounter =>
{
for (int rowCounter = 0; rowCounter < image.Cols; rowCounter++)
{
KuwaharaPixelProcessing pixelProcessor = new KuwaharaPixelProcessing(rowCounter, columnCounter, source, _kernel);
image.Data[columnCounter, rowCounter] = pixelProcessor.CalculatedPixelValue();
}
});
});
syncTask.RunSynchronously();
return(image);
}
public Image Step14DrawUltraSoundApproximation(ref VerificationStatus result, int relativeEstimationLimit)
{
if (!_debugMode)
{
throw new Exception("Can`t use this method in production mode");
}
ReflectionedLine drawingLine = _workingUltrasoundModA.ApproxLine;
SimpleGrayImage approxImage = new SimpleGrayImage(_workingUltrasoundModA.Image.Data);
IntPoint startPoint = new IntPoint(drawingLine.GetX(ModATopIndention), ModATopIndention);
IntPoint endPoint = new IntPoint(drawingLine.GetX(_workingUltrasoundModA.Image.Rows - ModABottomIndention),
_workingUltrasoundModA.Image.Rows - ModABottomIndention);
approxImage.DrawGrayLine(startPoint, endPoint, 128);
_ultrasoundModeAStatus = _workingUltrasoundModA.RelativeEstimation > relativeEstimationLimit ? VerificationStatus.Correct : VerificationStatus.Incorrect;
result = _ultrasoundModeAStatus;
return(approxImage.Bitmap);
}
public static Bitmap MorphologyNiblackBinarization(this Bitmap image, double k, int radius, int morphologyKernel, byte globalThreshold)
{
if (image.PixelFormat != PixelFormat.Format8bppIndexed)
{
throw new NotSupportedException("Filter can be applied to binary 8bpp images only");
}
Erosion morphologyErosion = new Erosion();
Bitmap tempMorphologyImage = morphologyErosion.Apply(image);
for (int i = 0; i < morphologyKernel - 1; i++)
{
tempMorphologyImage = morphologyErosion.Apply(tempMorphologyImage);
}
SimpleGrayImage morphologyImage = new SimpleGrayImage(tempMorphologyImage);
var threshold = new NiblackThreshold()
{
K = k, Radius = radius
};
SimpleGrayImage localBinImage = new SimpleGrayImage(threshold.Apply(image));
for (int i = 0; i < morphologyImage.Cols; i++)
{
for (int j = 0; j < morphologyImage.Rows; j++)
{
if (morphologyImage.Data[j, i] > globalThreshold)
{
morphologyImage.Data[j, i] = 255;
}
else
{
morphologyImage.Data[j, i] = localBinImage.Data[j, i];
}
}
}
return(morphologyImage.Bitmap);
}
public SimpleGrayImage Apply(SimpleGrayImage image)
{
//SimpleGrayImage source = image;
SimpleGrayImage source = new SimpleGrayImage(image.Data);
/*Parallel.For(0, image.Rows, columnCounter =>
* {
* for (int rowCounter = 0; rowCounter < image.Cols; rowCounter++)
* {
* //LgbtPixelProcessing pixelProcessor = new LgbtPixelProcessing(rowCounter, columnCounter, image, k, localRadius, globalRadius, globalThreshold);
* //image.Data[columnCounter, rowCounter] = pixelProcessor.CalculatedPixelValue();
* LgbtPixelProcessing pixelProcessor = new LgbtPixelProcessing(rowCounter, columnCounter, source, k, localRadius, globalRadius, globalThreshold);
* image.Data[columnCounter, rowCounter] = pixelProcessor.CalculatedPixelValue();
* }
* }
* );
*/
var syncTask = new Task(() =>
{
Parallel.For(0, image.Rows, j =>
{
for (int i = 0; i < image.Cols; i++)
{
//LgbtPixelProcessing pixelProcessor = new LgbtPixelProcessing(rowCounter, columnCounter, image, k, localRadius, globalRadius, globalThreshold);
//image.Data[columnCounter, rowCounter] = pixelProcessor.CalculatedPixelValue();
LgbtPixelProcessing pixelProcessor = new LgbtPixelProcessing(j, i, source, _k, _localRadius, _globalRadius, _globalThreshold);
image.Data[j, i] = pixelProcessor.CalculatedPixelValue();
}
});
});
syncTask.RunSynchronously();
return(image);
}
public UltrasoundModA(SimpleGrayImage image, int topIndention, int bottomIndention)
{
Image = image;
_topLine = topIndention;
_bottomLine = image.Rows - bottomIndention;
}
public Elastogram(SimpleGrayImage image)
{
Image = image;
}
