public void Apply()
{
string output_dir = @"C:\Users\yaoyichi\Desktop\";
string inputPath = output_dir + "1.png";
Log.SetLogDir(output_dir);
Log.SetOutputDir(output_dir);
HoughCircleTransformation circleTransform = new HoughCircleTransformation(35);
// apply Hough circle transform
Bitmap srcimg = new Bitmap(inputPath);
AForge.Imaging.Filters.BradleyLocalThresholding bradley = new AForge.Imaging.Filters.BradleyLocalThresholding();
Image <Gray, Byte> img = new Image <Gray, Byte>(inputPath);
Bitmap dstimg = bradley.Apply(img.Bitmap);
circleTransform.ProcessImage(dstimg);
Bitmap houghCirlceImage = circleTransform.ToBitmap();
// get circles using relative intensity
HoughCircle[] circles = circleTransform.GetCirclesByRelativeIntensity(0.2);
Graphics g = Graphics.FromImage(ImageUtils.AnyToFormat24bppRgb(srcimg));
foreach (HoughCircle circle in circles)
{
//circle.RelativeIntensity
g.DrawEllipse(new Pen(Color.Red), circle.X, circle.Y, circle.Radius, circle.Radius);
}
g.Dispose();
srcimg.Save(output_dir + "1_.png");
}
public static string ApplyBradleyLocalThresholding(string inputPath, string outputPath)
{
AForge.Imaging.Filters.BradleyLocalThresholding bradley = new AForge.Imaging.Filters.BradleyLocalThresholding();
Image<Gray, Byte> img = new Image<Gray, Byte>(inputPath);
Bitmap dstimg = bradley.Apply(img.Bitmap);
dstimg.Save(outputPath);
dstimg.Dispose();
dstimg = null;
img.Dispose();
img = null;
return outputPath;
}
public static string ApplyBradleyLocalThresholding(string inputPath, string outputPath)
{
AForge.Imaging.Filters.BradleyLocalThresholding bradley = new AForge.Imaging.Filters.BradleyLocalThresholding();
Image <Gray, Byte> img = new Image <Gray, Byte>(inputPath);
Bitmap dstimg = bradley.Apply(img.Bitmap);
dstimg.Save(outputPath);
dstimg.Dispose();
dstimg = null;
img.Dispose();
img = null;
return(outputPath);
}
public static void test(String directory)
{
ColorSegmentationWorker cs = new ColorSegmentationWorker();
//cs.Apply(@"C:\Users\yaoyichi\Desktop\", @"C:\Users\yaoyichi\Desktop\", "WMSImage_ms.png");
// AForge.Imaging.Filters.OtsuThreshold otsu = new AForge.Imaging.Filters.OtsuThreshold();
AForge.Imaging.Filters.BradleyLocalThresholding bradley = new AForge.Imaging.Filters.BradleyLocalThresholding();
Image<Gray, Byte> img = new Image<Gray, Byte>(@"C:\Users\yaoyichi\Desktop\Images-22-10\576800_mc1024_k64.png");
Bitmap dstimg =bradley.Apply(img.Bitmap);
dstimg.Save(@"C:\Users\yaoyichi\Desktop\Images-22-10\576800_mc1024_k64-2.png");
// Image<Gray, Byte> img = new Image<Gray, Byte>(@"C:\Users\yaoyichi\Desktop\Images-22-10\576800_mc1024_k64.png");
img = img.ThresholdAdaptive(new Gray(255),
Emgu.CV.CvEnum.ADAPTIVE_THRESHOLD_TYPE.CV_ADAPTIVE_THRESH_GAUSSIAN_C,Emgu.CV.CvEnum.THRESH.CV_THRESH_BINARY,15,new Gray(0));
img.Save(@"C:\Users\yaoyichi\Desktop\Images-22-10\576800_mc1024_k64-1.png");
}
public static void test(String directory)
{
ColorSegmentationWorker cs = new ColorSegmentationWorker();
//cs.Apply(@"C:\Users\yaoyichi\Desktop\", @"C:\Users\yaoyichi\Desktop\", "WMSImage_ms.png");
// AForge.Imaging.Filters.OtsuThreshold otsu = new AForge.Imaging.Filters.OtsuThreshold();
AForge.Imaging.Filters.BradleyLocalThresholding bradley = new AForge.Imaging.Filters.BradleyLocalThresholding();
Image <Gray, Byte> img = new Image <Gray, Byte>(@"C:\Users\yaoyichi\Desktop\Images-22-10\576800_mc1024_k64.png");
Bitmap dstimg = bradley.Apply(img.Bitmap);
dstimg.Save(@"C:\Users\yaoyichi\Desktop\Images-22-10\576800_mc1024_k64-2.png");
// Image<Gray, Byte> img = new Image<Gray, Byte>(@"C:\Users\yaoyichi\Desktop\Images-22-10\576800_mc1024_k64.png");
img = img.ThresholdAdaptive(new Gray(255),
Emgu.CV.CvEnum.ADAPTIVE_THRESHOLD_TYPE.CV_ADAPTIVE_THRESH_GAUSSIAN_C, Emgu.CV.CvEnum.THRESH.CV_THRESH_BINARY, 15, new Gray(0));
img.Save(@"C:\Users\yaoyichi\Desktop\Images-22-10\576800_mc1024_k64-1.png");
}
public Bitmap Process(Bitmap image)
{
Bitmap filteredImage = convertFormatTo32(image);
if (filterLevel >= 0)
{
filteredImage = resize(filteredImage, ImageSize.Width, ImageSize.Height);
}
if (filterLevel >= 1)
{
if (ContrastStretch)
{
AForge.Imaging.Filters.ContrastStretch stretcher = new AForge.Imaging.Filters.ContrastStretch();
filteredImage = stretcher.Apply(filteredImage);
}
if (Histogram)
{
AForge.Imaging.Filters.HistogramEqualization histogrammer = new AForge.Imaging.Filters.HistogramEqualization();
filteredImage = histogrammer.Apply(filteredImage);
}
if (Gaussian)
{
AForge.Imaging.Filters.GaussianBlur blurrer = new AForge.Imaging.Filters.GaussianBlur();
blurrer.Size = (int)GaussianStrength;
filteredImage = blurrer.Apply(filteredImage);
}
if (ContrastAdjustment)
{
AForge.Imaging.Filters.ContrastCorrection contraster = new AForge.Imaging.Filters.ContrastCorrection();
contraster.Factor = (float)ContrastStrength;
filteredImage = contraster.Apply(filteredImage);
}
if (Greyscale)
{
filteredImage = AForge.Imaging.Filters.Grayscale.CommonAlgorithms.BT709.Apply(filteredImage);
//Greyscale downgrades format
// filteredImage = convertFormatTo32(filteredImage.InternalBitmap);
}
if (Threshold)
{
//filteredImage.InternalBitmap = convertFormatToGS(filteredImage.InternalBitmap);
AForge.Imaging.Filters.Threshold thresholder = new AForge.Imaging.Filters.Threshold();
thresholder.ThresholdValue = (int)(((double)ThresholdStrength / 10.0) * 255.0);
filteredImage = thresholder.Apply(filteredImage);
}
if (Bradley)
{
AForge.Imaging.Filters.BradleyLocalThresholding bradlifier = new AForge.Imaging.Filters.BradleyLocalThresholding();
filteredImage = bradlifier.Apply(filteredImage);
}
}
return filteredImage;
}
