private String ContainGreen(Bitmap bitmap)
{
HSLFiltering filter = new HSLFiltering();
// set color ranges to keep
filter.Hue = new IntRange(80, 150);
filter.Saturation = new Range(0.4f, 1);
filter.Luminance = new Range(0.2f, 0.7f);
filter.ApplyInPlace(bitmap);
AForge.Imaging.BlobCounter blobCounterGreen = new AForge.Imaging.BlobCounter();
blobCounterGreen.FilterBlobs = true;
blobCounterGreen.ObjectsOrder = ObjectsOrder.Area;
blobCounterGreen.MinHeight = 10;
blobCounterGreen.MinWidth = 10;
blobCounterGreen.ProcessImage(bitmap);
//capturedPhotoGreen.Source = (WriteableBitmap)bitmap;
AForge.Imaging.Blob[] blobsGreen = blobCounterGreen.GetObjectsInformation();
for (int iBlob = 0; iBlob < blobsGreen.Length; iBlob++)
{
for (int jBlob = iBlob + 1; jBlob < blobsGreen.Length; jBlob++)
{
if ((Math.Abs(blobsGreen[iBlob].CenterOfGravity.X - blobsGreen[jBlob].CenterOfGravity.X) < blobsGreen[iBlob].Rectangle.Width / 2) &&
(Math.Abs(blobsGreen[iBlob].CenterOfGravity.Y - blobsGreen[jBlob].CenterOfGravity.Y) < 3 * blobsGreen[iBlob].Rectangle.Height) &&
(Math.Abs(blobsGreen[iBlob].Area - blobsGreen[jBlob].Area) < blobsGreen[iBlob].Area / 2))
{
//try { text_log.Text += "i" + iBlob + "j" + jBlob + "diff" + Math.Abs(blobsGreen[iBlob].CenterOfGravity.X - blobsGreen[jBlob].CenterOfGravity.X) + "w" + blobsGreen[iBlob].Rectangle.Width / 2; }
//catch (Exception ex) { text_log.Text = ex + ""; }
return("Green");
}
}
}
//text_log.Text += "nG";
return("");
}
public override void calcDescriptorInfo(Bitmap inImage)
{
shapeCount = new int[6];
originalImage = image;
image = imgProcessor.preProcessImage(inImage);
g = Graphics.FromImage(originalImage);
BlobCounter bCounter = new BlobCounter();
bCounter.ProcessImage(image);
Blob[] blobs = bCounter.GetObjectsInformation();
SimpleShapeChecker shapeChecker = new SimpleShapeChecker();
for (int i = 0; i < blobs.Length; i++)
{
if (blobs[i].Area < 100)
{
continue;
}
List<IntPoint> edgePts = bCounter.GetBlobsEdgePoints(blobs[i]);
checkShape(shapeChecker, edgePts);
}
g.Dispose();
}
public void DetectShapes()
{
int count = 40;
int minSize = 5;
int maxSize = 80;
var image = (Bitmap)Image.FromFile(@"C:\Users\marco\Downloads\PanoBeam\capture_pattern0.png");
Rectangle clippingRectangle = new Rectangle(new Point(563, 360), new Size(1156, 382));
var clippingRectangleCorners = new[]
{
new AForge.IntPoint(clippingRectangle.X, clippingRectangle.Y),
new AForge.IntPoint(clippingRectangle.X + clippingRectangle.Width, clippingRectangle.Y),
new AForge.IntPoint(clippingRectangle.X + clippingRectangle.Width, clippingRectangle.Y + clippingRectangle.Height),
new AForge.IntPoint(clippingRectangle.X, clippingRectangle.Y + clippingRectangle.Height)
};
Helpers.FillOutsideBlack(image, clippingRectangleCorners);
var blobCounter = new AForge.Imaging.BlobCounter();
AForge.Imaging.Blob[] blobs;
blobCounter.FilterBlobs = true;
blobCounter.MaxHeight = maxSize;
blobCounter.MaxWidth = maxSize;
blobCounter.MinHeight = minSize;
blobCounter.MinWidth = minSize;
var threshold = Recognition.GetThreshold(image);
blobCounter.BackgroundThreshold = Color.FromArgb(255, threshold, threshold, threshold);
blobCounter.ProcessImage(image);
blobs = blobCounter.GetObjectsInformation();
}
private String ContainBlue(Bitmap bitmap)
{
HSLFiltering blueFilter = new HSLFiltering();
blueFilter.Hue = new IntRange(150, 210);
blueFilter.Saturation = new Range(0.3f, 1);
blueFilter.Luminance = new Range(0.20f, 0.8f);
blueFilter.ApplyInPlace(bitmap);
AForge.Imaging.BlobCounter blobCounterBlue = new AForge.Imaging.BlobCounter();
blobCounterBlue.FilterBlobs = true;
blobCounterBlue.ObjectsOrder = ObjectsOrder.Area;
blobCounterBlue.MinHeight = 10;
blobCounterBlue.MinWidth = 10;
blobCounterBlue.ProcessImage(bitmap);
//capturedPhotoBlue.Source = (WriteableBitmap)bitmap;
AForge.Imaging.Blob[] blobsBlue = blobCounterBlue.GetObjectsInformation();
for (int iBlob = 0; iBlob < blobsBlue.Length; iBlob++)
{
for (int jBlob = iBlob + 1; jBlob < blobsBlue.Length; jBlob++)
{
if ((Math.Abs(blobsBlue[iBlob].CenterOfGravity.X - blobsBlue[jBlob].CenterOfGravity.X) < blobsBlue[iBlob].Rectangle.Width / 2) &&
(Math.Abs(blobsBlue[iBlob].CenterOfGravity.Y - blobsBlue[jBlob].CenterOfGravity.Y) < 3 * blobsBlue[iBlob].Rectangle.Height) &&
(Math.Abs(blobsBlue[iBlob].Area - blobsBlue[jBlob].Area) < blobsBlue[iBlob].Area / 2))
{
//try { text_log.Text += "i" + iBlob + "j" + jBlob + "diff" + Math.Abs(blobsBlue[iBlob].CenterOfGravity.X - blobsBlue[jBlob].CenterOfGravity.X) + "w" + blobsBlue[iBlob].Rectangle.Width / 2; }
//catch (Exception ex) { text_log.Text = ex + ""; }
return("Blue");
}
}
}
return("");
}
private void colorOfPlayer(Bitmap bitmap)
{
HSLFiltering GreenFilter = new HSLFiltering();
GreenFilter.Hue = new IntRange(200, 250);
GreenFilter.Saturation = new Range(0.5f, 1);
GreenFilter.Luminance = new Range(0.2f, 0.6f);
GreenFilter.ApplyInPlace(bitmap);
wbt = (WriteableBitmap)bitmap;
img2.Source = wbt;
img2.Visibility = Visibility.Visible;
// this.PictureBox.Source = (ImageSource)concatenate.Apply(this.img2);
BlobCounter blobCounter = new AForge.Imaging.BlobCounter();
blobCounter.ObjectsOrder = ObjectsOrder.Area;
blobCounter.FilterBlobs = true;
blobCounter.MinHeight = 10;
blobCounter.MinWidth = 10;
blobCounter.ProcessImage(bitmap);
Blob[] blobs = blobCounter.GetObjectsInformation();
SimpleShapeChecker shapeChecker = new SimpleShapeChecker();
try {
for (int i = 0, n = blobs.Length; i < n; i++)
{
List <IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(blobs[i]);
AForge.Point center;
float radius;
// is circle ?
if (shapeChecker.IsCircle(edgePoints, out center, out radius))
{
if ((blobs[i].Area < 17000) && (blobs[i].Area > 3000))
{
score = score + 2;
}
else if ((blobs[i].Area < 3000) && (blobs[i].Area > 1300))
{
score = score + 4;
}
else if (blobs[i].Area < 1300)
{
score = score + 6;
}
}
}
}catch (Exception eeeee)
{
}
text_score.Text = "" + score;
}
/// <summary>
/// Celem metody jest przykadrowanie otrzymanego obrazka, tak aby widok zawierał jedynie kartkę papieru, oraz zwrócenie go do metody UploadFile
/// </summary>
/// <param name="img"></param>
/// <returns></returns>
public System.Drawing.Image CropImage(System.Drawing.Image img)
{
//DocumentSkewChecker skewChecker = new DocumentSkewChecker();
//double angle = skewChecker.GetSkewAngle(image);
//RotateBilinear rotationFilter = new RotateBilinear(-angle);
//rotationFilter.FillColor = Color.White;
//Bitmap rotatedImage = rotationFilter.Apply(image);
Bitmap image = new Bitmap(img);
UnmanagedImage grayImage = null;
if (image.PixelFormat == PixelFormat.Format8bppIndexed)
{
grayImage = UnmanagedImage.FromManagedImage(image);
}
else
{
grayImage = UnmanagedImage.Create(image.Width, image.Height,
PixelFormat.Format8bppIndexed);
Grayscale.CommonAlgorithms.BT709.Apply(UnmanagedImage.FromManagedImage(image), grayImage);
}
CannyEdgeDetector edgeDetector = new CannyEdgeDetector();
UnmanagedImage edgesImage = edgeDetector.Apply(grayImage);
OtsuThreshold thresholdFilter = new OtsuThreshold();
thresholdFilter.ApplyInPlace(edgesImage);
Dilatation DilatationFilter = new Dilatation();
DilatationFilter.Apply(edgesImage);
Opening OpeningFilter = new Opening();
OpeningFilter.Apply(edgesImage);
BlobCounter blobCounter = new BlobCounter();
blobCounter.MinHeight = 32;
blobCounter.MinWidth = 32;
blobCounter.FilterBlobs = true;
blobCounter.ObjectsOrder = ObjectsOrder.Size;
blobCounter.ProcessImage(edgesImage);
Blob[] blobs = blobCounter.GetObjectsInformation();
ExtractBiggestBlob BiggestBlob = new ExtractBiggestBlob();
Bitmap biggestBlobsImage = BiggestBlob.Apply(edgesImage.ToManagedImage());
AForge.IntPoint BiggestBlogCorners = BiggestBlob.BlobPosition;
Crop cropFilter = new Crop(new Rectangle(BiggestBlogCorners.X, BiggestBlogCorners.Y, biggestBlobsImage.Width, biggestBlobsImage.Height));
Bitmap croppedImage = cropFilter.Apply(image);
return croppedImage;
}
private Boolean colorOfPlayer(Bitmap bitmap)
{
Boolean ok = false;
HSLFiltering filterRed = new HSLFiltering();
filterRed.Hue = new IntRange(301, 9); //red at night (334, 40)
filterRed.Saturation = new Range(0.4f, 1); //0.55
filterRed.Luminance = new Range(0.1f, 0.68f); //75
filterRed.ApplyInPlace(bitmap);
AForge.Imaging.BlobCounter blobCounterRed = new AForge.Imaging.BlobCounter();
blobCounterRed.FilterBlobs = true;
blobCounterRed.ObjectsOrder = ObjectsOrder.Area;
blobCounterRed.MinHeight = 10;
blobCounterRed.MinWidth = 10;
try { blobCounterRed.ProcessImage(bitmap); } catch (Exception es) { gameUpdate.Text = "filter"; }
AForge.Imaging.Blob[] blobsRed = blobCounterRed.GetObjectsInformation();
//Mean filter = new Mean();
//// apply the filter
//filter.ApplyInPlace(bitmap);
bool fin = false;
try
{
for (int iBlob = 0; iBlob < blobsRed.Length; iBlob++)
{
for (int jBlob = iBlob + 1; jBlob < blobsRed.Length; jBlob++)
{
if ((Math.Abs(blobsRed[iBlob].CenterOfGravity.X - blobsRed[jBlob].CenterOfGravity.X) < blobsRed[iBlob].Rectangle.Width / 2) &&
(Math.Abs(blobsRed[iBlob].CenterOfGravity.Y - blobsRed[jBlob].CenterOfGravity.Y) < 3 * blobsRed[iBlob].Rectangle.Height) &&
(Math.Abs(blobsRed[iBlob].Area - blobsRed[jBlob].Area) < blobsRed[iBlob].Area / 2))
{
// gameUpdate.Text = "OK" + SharedInformation.myNumber + getPlayerNumberByColor("Red");
ortcExample.DoSendMessage(SharedInformation.myNumber + getPlayerNumberByColor("Red"));
fin = true;
return(true);
}
}
if (fin)
{
break;
}
}
}
catch (Exception es) {
gameUpdate.Text = "erreur";
}
return(ok);
}
private void colorOfPlayer2(Bitmap bitmap2)
{
Bitmap bit2 = null;
bit2 = bitmap2;
bool fin = false;
HSLFiltering filter = new HSLFiltering();
// set color ranges to keep
filter.Hue = new IntRange(150, 210);
filter.Saturation = new Range(0.3f, 1);
filter.Luminance = new Range(0.20f, 0.8f);
filter.ApplyInPlace(bit2);
AForge.Imaging.BlobCounter blobCounterGreen = new AForge.Imaging.BlobCounter();
blobCounterGreen.FilterBlobs = true;
blobCounterGreen.ObjectsOrder = ObjectsOrder.Area;
blobCounterGreen.MinHeight = 10;
blobCounterGreen.MinWidth = 10;
blobCounterGreen.ProcessImage(bit2);
AForge.Imaging.Blob[] blobsGreen = blobCounterGreen.GetObjectsInformation();
try
{
for (int iBlob = 0; iBlob < blobsGreen.Length; iBlob++)
{
for (int jBlob = iBlob + 1; jBlob < blobsGreen.Length; jBlob++)
{
if ((Math.Abs(blobsGreen[iBlob].CenterOfGravity.X - blobsGreen[jBlob].CenterOfGravity.X) < blobsGreen[iBlob].Rectangle.Width / 2) &&
(Math.Abs(blobsGreen[iBlob].CenterOfGravity.Y - blobsGreen[jBlob].CenterOfGravity.Y) < 3 * blobsGreen[iBlob].Rectangle.Height) &&
(Math.Abs(blobsGreen[iBlob].Area - blobsGreen[jBlob].Area) < blobsGreen[iBlob].Area / 2))
{
//gameUpdate.Text = "OK" + SharedInformation.myNumber + getPlayerNumberByColor("Blue");
ortcExample.DoSendMessage(SharedInformation.myNumber + getPlayerNumberByColor("Blue"));
fin = true;
break;
}
}
if (fin)
{
break;
}
}
}
catch (Exception es)
{
gameUpdate.Text = "erreur22";
}
}
// 如果活动返回值，则从 CodeActivity<TResult>
// 派生并从 Execute 方法返回该值。
protected override void Execute(CodeActivityContext context)
{
// create an instance of blob counter algorithm
BlobCounterBase bc = new BlobCounter();
// set filtering options
bc.FilterBlobs = true;
bc.MinWidth = context.GetValue(最小宽度);
bc.MinHeight = context.GetValue(最小高度);
// set ordering options
bc.ObjectsOrder = ObjectsOrder.Size;
// process binary image
bc.ProcessImage(context.GetValue(处理目标));
var blobs = bc.GetObjectsInformation();
context.SetValue(输出目标, blobs);
}
public static void Rectangle(WriteableBitmap bitmap, DrawingContext dc)
{
// locating objects
BlobCounter blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
blobCounter.MaxHeight = 375;
blobCounter.MaxWidth = 375;
System.Drawing.Bitmap image;
using (var stream = new MemoryStream())
{
var encoder = new JpegBitmapEncoder();
encoder.Frames.Add(BitmapFrame.Create(bitmap));
encoder.Save(stream);
image = new System.Drawing.Bitmap(stream);
}
blobCounter.ProcessImage(image);
Blob[] blobs = blobCounter.GetObjectsInformation();
// check for rectangles
SimpleShapeChecker shapeChecker = new SimpleShapeChecker();
foreach (var blob in blobs)
{
List<IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(blob);
List<IntPoint> cornerPoints;
// use the shape checker to extract the corner points
if (shapeChecker.IsQuadrilateral(edgePoints, out cornerPoints))
{
// only do things if the corners form a rectangle
if (shapeChecker.CheckPolygonSubType(cornerPoints) == PolygonSubType.Rectangle)
{
// here i use the graphics class to draw an overlay, but you
// could also just use the cornerPoints list to calculate your
// x, y, width, height values.
List<AForge.Point> Points = new List<AForge.Point>();
foreach (var point in cornerPoints)
{
Points.Add(new AForge.Point(point.X, point.Y));
}
var path = new PathFigure(new System.Windows.Point(Points.First().X, Points.First().Y), Points.Select(row => new System.Windows.Media.LineSegment(new System.Windows.Point(row.X, row.Y), false)), true);
dc.DrawGeometry(Brushes.Red, null, new PathGeometry(new PathFigure[] { path }));
}
}
}
}
public IEnumerable<Bitmap> Apply(Bitmap bitmap)
{
// assuming scanned background is white we need to invert for the algo to work
var copy = new Invert().Apply(bitmap);
copy = EnsureGrayscale(copy);
new Threshold { ThresholdValue = 25 }.ApplyInPlace(copy);
new FillHoles().ApplyInPlace(copy);
var blobCounter = new BlobCounter
{
// set filtering options
FilterBlobs = true,
MinWidth = 50,
MinHeight = 50,
};
blobCounter.ProcessImage(copy);
var blobs = blobCounter.GetObjectsInformation();
if (blobs.Any())
{
var invertedOriginal = new Invert().Apply(bitmap);
foreach (var blob in blobs)
{
// use inverted source to ensure correct edge colors
blobCounter.ExtractBlobsImage(invertedOriginal, blob, false);
var blobImage = blob.Image.ToManagedImage();
// straighten
var angle = new DocumentSkewChecker().GetSkewAngle(EnsureGrayscale(blobImage));
var rotationFilter = new RotateBilinear(-angle) { FillColor = Color.Black };
blobImage = rotationFilter.Apply(blobImage);
// crop
blobImage = new ExtractBiggestBlob().Apply(blobImage);
new Invert().ApplyInPlace(blobImage);
yield return blobImage;
}
}
else
{
yield return bitmap;
}
}
private WriteableBitmap FindPlate(IEnumerable<Rect> rects, WriteableBitmap image)
{
WriteableBitmap bestCandidate = null;
foreach (var rect in rects)
{
var croppedImage = image.Crop(rect);
var edgeFilter = new CannyEdgeDetector();
var smoothFilter = new Median();
var grayFilter = new Grayscale(0.2125, 0.7154, 0.0721);
var blobCounter = new BlobCounter();
var cutTop = croppedImage.PixelHeight * 0.3;
croppedImage = croppedImage.Crop(new Rect(0, cutTop, croppedImage.PixelWidth, croppedImage.PixelHeight));
var bitmap = (Bitmap)croppedImage;
var grayImage = grayFilter.Apply(bitmap);
bitmap = smoothFilter.Apply(grayImage);
edgeFilter.ApplyInPlace(bitmap);
blobCounter.ProcessImage(bitmap);
var blobs = blobCounter.GetObjectsInformation();
var possibleChars = new List<Rectangle>();
foreach (var blob in blobs)
{
var objRectangle = blob.Rectangle;
var ratio = (double)objRectangle.Height / (double)objRectangle.Width;
if (ratio >= 1.16d && ratio <= 6.3d)
{
possibleChars.Add(objRectangle);
}
}
if (possibleChars.Count == 0)
{
continue;
}
bestCandidate = croppedImage;
}
return bestCandidate;
}
private static Blob[] blobRecognition(Bitmap thresholdedInverted)
{
//Use the AForge.NET BlobCounter to perform Blob Recognition / Connected Region Analysis
BlobCounter blobRecognition = new BlobCounter();
//Filter out blobs that are abviously the wrong size to be characters
blobRecognition.MinWidth = (int)(thresholdedInverted.Width * (BLOB_FILTER_MIN_DIMENSION_IMAGE_PERCENTAGE / 100));
blobRecognition.MinHeight = (int)(thresholdedInverted.Height * (BLOB_FILTER_MIN_DIMENSION_IMAGE_PERCENTAGE / 100));
blobRecognition.MaxWidth = (int)(thresholdedInverted.Width * (BLOB_FILTER_MAX_DIMENSION_IMAGE_PERCENTAGE / 100));
blobRecognition.MaxHeight = (int)(thresholdedInverted.Height * (BLOB_FILTER_MAX_DIMENSION_IMAGE_PERCENTAGE / 100));
blobRecognition.FilterBlobs = true;
blobRecognition.ProcessImage(thresholdedInverted);
Blob[] blobs = blobRecognition.GetObjectsInformation();
return blobs;
}
public List<Blob> ExtractBlob()
{
// create instance of blob counter
BlobCounter blobCounter = new BlobCounter();
// process input image
blobCounter.ProcessImage(ImageBitmap);
// get information about detected objects
Blob[] blobArray = blobCounter.GetObjectsInformation();
foreach(Blob blobdata in blobArray)
{
blobCounter.ExtractBlobsImage(ImageBitmap, blobdata, true);
}
return blobArray.ToList();
}
Blob[] DetectBlobs(Bitmap bmp)
{
Invert filter = new Invert();
filter.ApplyInPlace(bmp);
BlobCounter bc = new BlobCounter();
bc.BackgroundThreshold = Color.FromArgb(8, 8, 8);
bc.BlobsFilter = new BlobsFilter(bmp.Size);
bc.FilterBlobs = true;
bc.ProcessImage(bmp);
// Revert back
filter.ApplyInPlace(bmp);
return bc.GetObjectsInformation();
}
// Process specified image trying to recognize counter's image
public void Process(Bitmap image, IImageProcessingLog log)
{
log.AddMessage("Image size: " + image.Width +
" x " + image.Height);
//get image
byte[] textData = GetImageData();
UnmanagedImage img = CreateImage(textData);
log.AddImage("Raw Image", img.ToManagedImage());
//resize Image
AForge.Imaging.Filters.ResizeNearestNeighbor resizeFilter = new AForge.Imaging.Filters.ResizeNearestNeighbor(500, (int)(500 / res));
UnmanagedImage resizedImage = resizeFilter.Apply(img);
log.AddImage("Resized Image", resizedImage.ToManagedImage());
//filter floor
UnmanagedImage floorFilteredImage = FilterFloor(resizedImage, textData);
log.AddImage("Floor filtered", floorFilteredImage.ToManagedImage());
// 1- grayscale image
Bitmap grayImage =
Grayscale.CommonAlgorithms.BT709.Apply(resizedImage.ToManagedImage());
log.AddImage("Grayscale", resizedImage.ToManagedImage());
// 2 - Otsu thresholding
OtsuThreshold threshold = new OtsuThreshold();
Bitmap binaryImage = threshold.Apply(grayImage);
log.AddImage("Binary", binaryImage);
log.AddMessage("Otsu threshold: " + threshold.ThresholdValue);
//resive image
// 3 - Blob counting
BlobCounter blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
blobCounter.MinWidth = 1;
blobCounter.MinWidth = 1;
blobCounter.ProcessImage(binaryImage);
Blob[] blobs = blobCounter.GetObjectsInformation();
log.AddMessage("Found blobs (min width/height = 24): " +
blobs.Length);
}
public Bitmap ProcessFrame(Bitmap inputBitmap, int x, int y)
{
// Create an image for AForge to process
Bitmap workingImage = new Bitmap(inputBitmap.Width, inputBitmap.Height);
workingImage = AForge.Imaging.Image.Clone(inputBitmap, PixelFormat.Format24bppRgb);
// Create a mask for ROI selection
Rectangle roi = new Rectangle(x - 30, y-30, 80, 80);
Crop roicrop = new Crop(roi);
Bitmap outimage = roicrop.Apply(workingImage);
BlobCounter blobCounter = new BlobCounter();
blobCounter.ObjectsOrder = ObjectsOrder.Area;
Blob[] blobs;
// Find the blobs
blobCounter.ProcessImage(outimage);
blobs = blobCounter.GetObjectsInformation();
List<IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(blobs[0]);
GrahamConvexHull grahamScan = new GrahamConvexHull();
List<IntPoint> hullPoints = grahamScan.FindHull(edgePoints);
Graphics g = Graphics.FromImage(outimage);
Pen redPen = new Pen(Color.Red, 2);
g.DrawPolygon(redPen, ToPointsArray(hullPoints));
//g.Clear(Color.Black);
//g.DrawImage(handImage, x, y);
//g.DrawRectangle(redPen, roi);
//g.DrawEllipse(redPen, x, y, 20, 20);
ResizeNearestNeighbor resizeFilter = new ResizeNearestNeighbor(160, 160);
Bitmap resizedImage = resizeFilter.Apply(outimage);
return resizedImage;
}
public List<Blob> ExtractBlob(int maxWidth, int maxHeight, int minWidth, int minHeight)
{
BlobCounter blobCounter = new BlobCounter();
blobCounter.MinHeight = minHeight;
blobCounter.MinWidth = minWidth;
blobCounter.MaxWidth = maxWidth;
blobCounter.MaxHeight = maxHeight;
blobCounter.FilterBlobs = true;
// process input image
blobCounter.ProcessImage(ImageBitmap);
// get information about detected objects
Blob[] blobArray = blobCounter.GetObjectsInformation();
foreach (Blob blobdata in blobArray)
{
blobCounter.ExtractBlobsImage(ImageBitmap, blobdata, true);
}
return blobArray.ToList();
}
public static List<List<IntPoint>> Quadrilaterals(Bitmap img, int minWidth, int minHeight)
{
Bitmap thresholdedImg = FilterCombinations.AdaptiveThreshold(img);
//Use blob recognition on the image to find all blobs meeting the specified minimum width & height
BlobCounter blobCounter = new BlobCounter();
//Filter out small blobs
blobCounter.MinWidth = minWidth;
blobCounter.MinHeight = minHeight;
blobCounter.FilterBlobs = true;
//Order the blobs by size (desc), as since we're looking for quads of a minimum size, it's likely we'll be more interested in the laregr ones
blobCounter.ObjectsOrder = ObjectsOrder.Size;
//Check if each blob is approximately a quadriateral, and if so store the 4 corners
List<List<IntPoint>> foundQuads = new List<List<IntPoint>>();
//Shape checker to be used to test if a blob is a quadrilateral
SimpleShapeChecker shapeChecker = new SimpleShapeChecker();
//Find the blobs
blobCounter.ProcessImage(thresholdedImg);
Blob[] blobs = blobCounter.GetObjectsInformation();
foreach(Blob b in blobs)
{
List<IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(b);
List<IntPoint> corners = null;
//Is this blob approximately a quadrilateral?
if(shapeChecker.IsQuadrilateral(edgePoints, out corners))
{
//Store the Quad's corners
foundQuads.Add(corners);
}
}
return foundQuads;
}
public static AForge.Point GetRedBlobCenter(Bitmap image)
{
BlobCounter bCounter = new BlobCounter();
bCounter.ProcessImage(image);
Blob[] blobs = bCounter.GetObjectsInformation();
Rectangle[] rects = bCounter.GetObjectsRectangles();
Pen pen = new Pen(Color.Red, 2);
Brush brush = new SolidBrush(Color.Red);
Graphics g = Graphics.FromImage(image);
if (rects.Length > 0) { g.FillRectangle(brush, rects[0]); }
if (blobs.Length > 0)
{
detected = true;
lastPos = blobs[0].CenterOfGravity;
AForge.Point rPos = new AForge.Point();
rPos.Y = ((lastPos.Y / 5) / 100) * 768;
rPos.X = ((lastPos.X / 5) / 100) * 1366;
return rPos;
}
else
{
detected = false;
if (lastPos != null)
{
return lastPos;
}
else
{
return new AForge.Point(50.0f, 50.0f);
}
}
}
public Boolean ContainOrange(Bitmap bitmap)
{
ColorFiltering RedFilter = new ColorFiltering();
RedFilter.Red = new IntRange(100, 255);
RedFilter.Green = new IntRange(0, 100);
RedFilter.Blue = new IntRange(0, 100);
RedFilter.ApplyInPlace(bitmap);
AForge.Imaging.BlobCounter blobCounterGreen = new AForge.Imaging.BlobCounter();
blobCounterGreen.FilterBlobs = true;
blobCounterGreen.MinHeight = 5;
blobCounterGreen.MinWidth = 5;
blobCounterGreen.ProcessImage(bitmap);
AForge.Imaging.Blob[] blobsGreen = blobCounterGreen.GetObjectsInformation();
SimpleShapeChecker shapeCheckerGreen = new SimpleShapeChecker();
if (blobsGreen.Length > 0)
{
return(true);
}
return(false);
}
public String ContainRed(Bitmap bitmap)
{
HSLFiltering filterRed = new HSLFiltering();
filterRed.Hue = new IntRange(301, 9); //red at night (334, 40)
filterRed.Saturation = new Range(0.4f, 1); //0.55
filterRed.Luminance = new Range(0.1f, 0.68f); //75
filterRed.ApplyInPlace(bitmap);
AForge.Imaging.BlobCounter blobCounterRed = new AForge.Imaging.BlobCounter();
blobCounterRed.FilterBlobs = true;
blobCounterRed.ObjectsOrder = ObjectsOrder.Area;
blobCounterRed.MinHeight = 10;
blobCounterRed.MinWidth = 10;
blobCounterRed.ProcessImage(bitmap);
AForge.Imaging.Blob[] blobsRed = blobCounterRed.GetObjectsInformation();
//capturedPhotoRed.Source = (WriteableBitmap)bitmap;
//Mean filter = new Mean();
//// apply the filter
//filter.ApplyInPlace(bitmap);
for (int iBlob = 0; iBlob < blobsRed.Length; iBlob++)
{
for (int jBlob = iBlob + 1; jBlob < blobsRed.Length; jBlob++)
{
if ((Math.Abs(blobsRed[iBlob].CenterOfGravity.X - blobsRed[jBlob].CenterOfGravity.X) < blobsRed[iBlob].Rectangle.Width / 2) &&
(Math.Abs(blobsRed[iBlob].CenterOfGravity.Y - blobsRed[jBlob].CenterOfGravity.Y) < 3 * blobsRed[iBlob].Rectangle.Height) &&
(Math.Abs(blobsRed[iBlob].Area - blobsRed[jBlob].Area) < blobsRed[iBlob].Area / 2))
{
//try { text_log.Text += "i" + iBlob + "j" + jBlob + "diff" + Math.Abs(blobsRed[iBlob].CenterOfGravity.X - blobsRed[jBlob].CenterOfGravity.X) + "w" + blobsRed[iBlob].Rectangle.Width / 2; }
//catch (Exception ex) { text_log.Text = ex + ""; }
return("red");
}
}
}
return("");
}
public String ContainPurple(Bitmap bitmap)
{
HSLFiltering filter = new HSLFiltering();
// set color ranges to keep
filter.Hue = new IntRange(220, 290);
filter.Saturation = new Range(0.4f, 0.8f);
filter.Luminance = new Range(0.35f, 0.78f);
filter.ApplyInPlace(bitmap);
AForge.Imaging.BlobCounter blobCounterPutple = new AForge.Imaging.BlobCounter();
blobCounterPutple.FilterBlobs = true;
blobCounterPutple.ObjectsOrder = ObjectsOrder.Area;
blobCounterPutple.MinHeight = 10;
blobCounterPutple.MinWidth = 10;
blobCounterPutple.ProcessImage(bitmap);
AForge.Imaging.Blob[] blobsPurple = blobCounterPutple.GetObjectsInformation();
SimpleShapeChecker shapeCheckerPurple = new SimpleShapeChecker();
//capturedPhotoBlue.Source = (WriteableBitmap)bitmap;
for (int iBlob = 0; iBlob < blobsPurple.Length; iBlob++)
{
for (int jBlob = iBlob + 1; jBlob < blobsPurple.Length; jBlob++)
{
if ((Math.Abs(blobsPurple[iBlob].CenterOfGravity.X - blobsPurple[jBlob].CenterOfGravity.X) < blobsPurple[iBlob].Rectangle.Width / 2) &&
(Math.Abs(blobsPurple[iBlob].CenterOfGravity.Y - blobsPurple[jBlob].CenterOfGravity.Y) < 3 * blobsPurple[iBlob].Rectangle.Height) &&
(Math.Abs(blobsPurple[iBlob].Area - blobsPurple[jBlob].Area) < blobsPurple[iBlob].Area / 2))
{
//try { text_log.Text += "i" + iBlob + "j" + jBlob + "diff" + Math.Abs(blobsPurple[iBlob].CenterOfGravity.X - blobsPurple[jBlob].CenterOfGravity.X) + "w" + blobsPurple[iBlob].Rectangle.Width / 2; }
//catch (Exception ex) { text_log.Text = ex + ""; }
return("Purple");
}
}
}
return("");
}
// =========================================================
private Bitmap DrawRectanglesFunct(Bitmap image)
{
// step 1 - turn background to black (done)
// step 2 - locating objects
BlobCounter blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
blobCounter.MinHeight = 3;
blobCounter.MinWidth = 3;
blobCounter.ProcessImage(image);
Blob[] blobs = blobCounter.GetObjectsInformation();
// step 3 - check objects' type and do what you do:
Graphics g = Graphics.FromImage(image);
Pen pen = new Pen(Color.DarkOrange, 2);
for (int i = 0, n = blobs.Length; i < n; i++)
{
SimpleShapeChecker ShapeChecker = new SimpleShapeChecker();
List<IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(blobs[i]);
List<IntPoint> cornerPoints;
// fine tune ShapeChecker
ShapeChecker.AngleError = 15; // default 7
ShapeChecker.LengthError = 0.3F; // default 0.1 (10%)
ShapeChecker.MinAcceptableDistortion = 0.9F; // in pixels, default 0.5
ShapeChecker.RelativeDistortionLimit = 0.2F; // default 0.03 (3%)
// use the Outline checker to extract the corner points
if (ShapeChecker.IsQuadrilateral(edgePoints, out cornerPoints))
{
// only do things if the corners form a rectangle
if (ShapeChecker.CheckPolygonSubType(cornerPoints) == PolygonSubType.Rectangle)
{
List<IntPoint> corners = PointsCloud.FindQuadrilateralCorners(edgePoints);
g.DrawPolygon(pen, ToPointsArray(corners));
}
}
}
return (image);
}
// ==========================================================================================================
// Components:
// ==========================================================================================================
private List<Shapes.Component> FindComponentsFunct(Bitmap bitmap)
{
// Locating objects
BlobCounter blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
blobCounter.MinHeight = 8;
blobCounter.MinWidth = 8;
blobCounter.ProcessImage(bitmap);
Blob[] blobs = blobCounter.GetObjectsInformation();
// create convex hull searching algorithm
GrahamConvexHull hullFinder = new GrahamConvexHull();
ClosePointsMergingOptimizer optimizer1 = new ClosePointsMergingOptimizer();
FlatAnglesOptimizer optimizer2 = new FlatAnglesOptimizer();
List<Shapes.Component> Components = new List<Shapes.Component>();
// process each blob
foreach (Blob blob in blobs)
{
List<IntPoint> leftPoints, rightPoints, edgePoints = new List<IntPoint>();
if ((blob.Rectangle.Height > 400) && (blob.Rectangle.Width > 600))
{
break; // The whole image could be a blob, discard that
}
// get blob's edge points
blobCounter.GetBlobsLeftAndRightEdges(blob,
out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
// blob's convex hull
List<IntPoint> Outline = hullFinder.FindHull(edgePoints);
optimizer1.MaxDistanceToMerge = 4;
optimizer2.MaxAngleToKeep = 170F;
Outline = optimizer2.OptimizeShape(Outline);
Outline = optimizer1.OptimizeShape(Outline);
// find Longest line segment
float dist = 0;
LineSegment Longest = new LineSegment(Outline[0], Outline[1]);
LineSegment line;
dist = Longest.Length;
int LongestInd = 0;
for (int i = 1; i < Outline.Count; i++)
{
if (i != Outline.Count - 1)
{
line = new LineSegment(Outline[i], Outline[i + 1]);
}
else
{
// last iteration
if (Outline[i] == Outline[0])
{
break;
}
line = new LineSegment(Outline[i], Outline[0]);
}
if (line.Length > dist)
{
Longest = line;
dist = line.Length;
LongestInd = i;
}
}
// Get the center point of it
AForge.Point LongestCenter = new AForge.Point();
LongestCenter.X = (float)Math.Round((Longest.End.X - Longest.Start.X) / 2.0 + Longest.Start.X);
LongestCenter.Y = (float)Math.Round((Longest.End.Y - Longest.Start.Y) / 2.0 + Longest.Start.Y);
AForge.Point NormalStart = new AForge.Point();
AForge.Point NormalEnd = new AForge.Point();
// Find normal:
// start= longest.start rotated +90deg relative to center
// end= longest.end rotated -90deg and relative to center
// If you rotate point (px, py) around point (ox, oy) by angle theta you'll get:
// p'x = cos(theta) * (px-ox) - sin(theta) * (py-oy) + ox
// p'y = sin(theta) * (px-ox) + cos(theta) * (py-oy) + oy
// cos90 = 0, sin90= 1 =>
// p'x= -(py-oy) + ox= oy-py+ox, p'y= (px-ox)+ oy
NormalStart.X = LongestCenter.Y - Longest.Start.Y + LongestCenter.X;
NormalStart.Y = (Longest.Start.X - LongestCenter.X) + LongestCenter.Y;
// cos-90=0, sin-90= -1 =>
// p'x= (py-oy) + ox
// p'y= -(px-ox)+oy= ox-px+oy
NormalEnd.X = (Longest.Start.Y - LongestCenter.Y) + LongestCenter.X;
NormalEnd.Y = LongestCenter.X - Longest.Start.X + LongestCenter.Y;
// Make line out of the points
Line Normal = Line.FromPoints(NormalStart, NormalEnd);
// Find the furthest intersection to the normal (skip the Longest)
AForge.Point InterSection = new AForge.Point();
AForge.Point Furthest = new AForge.Point();
bool FurhtestAssinged = false;
LineSegment seg;
dist = 0;
for (int i = 0; i < Outline.Count; i++)
{
if (i == LongestInd)
{
continue;
}
if (i != Outline.Count - 1)
{
seg = new LineSegment(Outline[i], Outline[i + 1]);
}
else
{
// last iteration
if (Outline[i] == Outline[0])
{
break;
}
seg = new LineSegment(Outline[i], Outline[0]);
}
if (seg.GetIntersectionWith(Normal) == null)
{
continue;
}
InterSection = (AForge.Point)seg.GetIntersectionWith(Normal);
if (InterSection.DistanceTo(LongestCenter) > dist)
{
Furthest = InterSection;
FurhtestAssinged = true;
dist = InterSection.DistanceTo(LongestCenter);
}
}
// Check, if there is a edge point that is close to the normal even further
AForge.Point fPoint = new AForge.Point();
for (int i = 0; i < Outline.Count; i++)
{
fPoint.X = Outline[i].X;
fPoint.Y = Outline[i].Y;
if (Normal.DistanceToPoint(fPoint) < 1.5)
{
if (fPoint.DistanceTo(LongestCenter) > dist)
{
Furthest = fPoint;
FurhtestAssinged = true;
dist = fPoint.DistanceTo(LongestCenter);
}
}
}
AForge.Point ComponentCenter = new AForge.Point();
if (FurhtestAssinged)
{
// Find the midpoint of LongestCenter and Furthest: This is the centerpoint of component
ComponentCenter.X = (float)Math.Round((LongestCenter.X - Furthest.X) / 2.0 + Furthest.X);
ComponentCenter.Y = (float)Math.Round((LongestCenter.Y - Furthest.Y) / 2.0 + Furthest.Y);
// Alignment is the angle of longest
double Alignment;
if (Math.Abs(Longest.End.X - Longest.Start.X) < 0.001)
{
Alignment = 0;
}
else
{
Alignment = Math.Atan((Longest.End.Y - Longest.Start.Y) / (Longest.End.X - Longest.Start.X));
Alignment = Alignment * 180.0 / Math.PI; // in deg.
}
Components.Add(new Shapes.Component(ComponentCenter, Alignment, Outline, Longest, NormalStart, NormalEnd));
}
}
return Components;
}
// ==========================================================================================================
// Circles:
// ==========================================================================================================
private List<Shapes.Circle> FindCirclesFunct(Bitmap bitmap)
{
// locating objects
BlobCounter blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
blobCounter.MinHeight = 5;
blobCounter.MinWidth = 5;
blobCounter.ProcessImage(bitmap);
Blob[] blobs = blobCounter.GetObjectsInformation();
List<Shapes.Circle> Circles = new List<Shapes.Circle>();
for (int i = 0, n = blobs.Length; i < n; i++)
{
SimpleShapeChecker shapeChecker = new SimpleShapeChecker();
List<IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(blobs[i]);
AForge.Point center;
float radius;
// is circle ?
if (shapeChecker.IsCircle(edgePoints, out center, out radius))
{
if (radius > 3) // MirrFilter out some noise
{
Circles.Add(new Shapes.Circle(center.X, center.Y, radius));
}
}
}
return (Circles);
}
private void FindCenterMarker()
{
List<Marker> _blobs = new List<Marker>();
//блокируем изображение в памяти
BitmapData bitmapData = _markersimg.LockBits(
new Rectangle(0, 0, _markersimg.Width, _markersimg.Height),
ImageLockMode.ReadWrite, _markersimg.PixelFormat);
BlobCounter blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
//устанавливаем фильтр и максимальные и минимальные размеры маркера
blobCounter.MinHeight = blobCounter.MinWidth = Geometry.MMtoPX(_makerdiameter - 2.0d, _image.VerticalResolution);
blobCounter.MaxHeight = blobCounter.MaxWidth = Geometry.MMtoPX(_makerdiameter + 3.0d, _image.VerticalResolution);
//собственно поиск
blobCounter.ProcessImage(bitmapData);
Blob[] blobs = blobCounter.GetObjectsInformation();
_markersimg.UnlockBits(bitmapData);
for (int i = 0, n = blobs.Length; i < n; i++)
{
if (blobs[i].Fullness > 0.3)
{
Marker tempmark = new Marker(blobs[i]);
_blobs.Add(tempmark);
}
}
this.RecognizeMarkers(_blobs);
}
/// <summary>
/// Scans dominant color on image and returns it.
/// Crops rank part on image and analyzes suit part on image
/// </summary>
/// <param name="bmp">Bitmap to be scanned</param>
/// <returns>Returns 'B' for black , 'R' for red</returns>
private char ScanColor(Bitmap bmp)
{
//System.Diagnostics.Debug.Flush();
//System.Diagnostics.Debug.Print("I'm here");
char color = 'B';
//Crop rank part
Crop crop = new Crop(new Rectangle(0, bmp.Height / 2, bmp.Width, bmp.Height / 2));
bmp = crop.Apply(bmp);
Bitmap temp = commonSeq.Apply(bmp); //Apply filters
//Find suit blob on image
BlobCounter counter = new BlobCounter();
counter.ProcessImage(temp);
Blob[] blobs = counter.GetObjectsInformation();
if (blobs.Length > 0) //If blobs found
{
Blob max = blobs[0];
//Find blob whose size is biggest
foreach (Blob blob in blobs)
{
if (blob.Rectangle.Height > max.Rectangle.Height)
max = blob;
else if (blob.Rectangle.Height == max.Rectangle.Height)
max = blob.Rectangle.Width > max.Rectangle.Width ? blob : max;
}
QuadrilateralTransformation trans = new QuadrilateralTransformation();
trans.SourceQuadrilateral = PointsCloud.FindQuadrilateralCorners(counter.GetBlobsEdgePoints(max));
bmp = trans.Apply(bmp); //Extract suit
}
//Lock Bits for processing
//int bitsPerPixel = ((int)bmp.PixelFormat & 0xff00) >> 8;
//int bytesPerPixel = (bitsPerPixel + 7) / 8;
//int stride = 4 * ((bmp.Width * bytesPerPixel + 3) / 4);
// BitmapData imageData=new BitmapData(bmp.Width, bmp.Height, bmp. )
// BitmapData imageData = bmp.LockBits(new Rectangle(0, 0, bmp.Width, bmp.Height),ImageLockMode.ReadOnly, bmp.PixelFormat);
int totalRed = 0;
int totalBlack = 0;
WriteableBitmap wbmp = (WriteableBitmap)bmp;
wbmp.ForEach((x, y, pcolor) =>
{
int r=Convert.ToInt32(pcolor.R);
int g=Convert.ToInt32(pcolor.G);
int b=Convert.ToInt32(pcolor.B);
if (r > g + b)
totalRed++;
else if (r <= g + b && (r < 50 && g < 50))
totalBlack++;
return pcolor;
});
if (totalRed > totalBlack) //If red is dominant
color = 'R'; //Set color as Red
return color;
}
/// <summary>
/// Detects and recognizes cards from source image
/// </summary>
/// <param name="source">Source image to be scanned</param>
/// <returns>Recognized Cards</returns>
public CardCollection Recognize(Bitmap source)
{
CardCollection collection = new CardCollection(); //Collection that will hold cards
Bitmap temp = source.Clone() as Bitmap; //Clone image to keep original image
FiltersSequence seq = new FiltersSequence();
seq.Add(Grayscale.CommonAlgorithms.BT709); //First add grayScaling filter
seq.Add(new OtsuThreshold()); //Then add binarization(thresholding) filter
temp = seq.Apply(source); // Apply filters on source image
//Extract blobs from image whose size width and height larger than 150
BlobCounter extractor = new BlobCounter();
extractor.FilterBlobs = true;
extractor.MinWidth = extractor.MinHeight = 150;
extractor.MaxWidth = extractor.MaxHeight = 350;
extractor.ProcessImage(temp);
//Will be used transform(extract) cards on source image
QuadrilateralTransformation quadTransformer = new QuadrilateralTransformation();
//Will be used resize(scaling) cards
ResizeBilinear resizer = new ResizeBilinear(CardWidth, CardHeight);
foreach (Blob blob in extractor.GetObjectsInformation())
{
//Get Edge points of card
List<IntPoint> edgePoints = extractor.GetBlobsEdgePoints(blob);
//Calculate/Find corners of card on source image from edge points
List<IntPoint> corners = PointsCloud.FindQuadrilateralCorners(edgePoints);
quadTransformer.SourceQuadrilateral = corners; //Set corners for transforming card
quadTransformer.AutomaticSizeCalculaton = true;
Bitmap cardImg = quadTransformer.Apply(source); //Extract(transform) card image
if (cardImg.Width > cardImg.Height) //If card is positioned horizontally
cardImg.RotateFlip(RotateFlipType.Rotate90FlipNone); //Rotate
cardImg = resizer.Apply(cardImg); //Normalize card size
Card card = new Card(cardImg, corners.ToArray()); //Create Card Object
bool faceCard = IsFaceCard(cardImg); //Determine type of card(face or not)
ResizeBicubic res;
seq.Clear();
seq.Add(Grayscale.CommonAlgorithms.BT709);
seq.Add(new OtsuThreshold());
Bitmap topLeftSuit = card.GetTopLeftSuitPart();
Bitmap bmp = seq.Apply(topLeftSuit);
bmp = CutWhiteSpaces(bmp);
res = new ResizeBicubic(32, 40);
bmp = res.Apply(bmp);
Bitmap topLeftRank = card.GetTopLeftRankPart();
Bitmap bmp2 = seq.Apply(topLeftRank);
bmp2 = CutWhiteSpaces(bmp2);
seq.Clear();
seq.Add(new OtsuThreshold());
bmp = seq.Apply(bmp);
card.Suit = ScanSuit(bmp);
if (!faceCard)
{
res = new ResizeBicubic(26, 40);
bmp2 = res.Apply(bmp2);
seq.Clear();
seq.Add(new OtsuThreshold());
bmp2 = seq.Apply(bmp2);
card.Rank = ScanRank(bmp2);
}
else
{
res = new ResizeBicubic(32, 40);
bmp2 = res.Apply(bmp2);
seq.Clear();
seq.Add(new OtsuThreshold());
bmp2 = seq.Apply(bmp2);
card.Rank = ScanFaceRank(bmp2);
}
collection.Add(card); //Add card to collection
}
return collection;
}
/// <summary>
/// Добавляет несколько несколько ячеек в ответ начиная с первой
/// </summary>
/// <param name="image">Ссылка ни изображение</param>
/// <param name="CellsCount">Количество ячеек для добавления в ответ</param>
/// <param name="FirstCellDistanses">Коллекция дистанций между первой ячейкой и маркерами</param>
/// <param name="intercentresdistX">Расстояние между центрами ячеек</param>
/// <param name="Width">Длина ячеек</param>
/// <param name="Height">Высота ячеек</param>
public void IntelligentAdd(Bitmap image, int CellsCount, Distances FirstCellDistanses, int intercentresdistX, int Width, int Height)
{
int maxslice = intercentresdistX/2;
//находим первую доступную дистанцию
Distance d = FirstCellDistanses.FindOneGood();
int maxWidth = Width + Convert.ToInt16(Width/2);
int maxHeigth = Height + Convert.ToInt16(Height/2);
//увеличиваем ячейки
this.Add(image,CellsCount,FirstCellDistanses,intercentresdistX,maxWidth,maxHeigth);
BitmapData data = image.LockBits(_cells[0].Rect, ImageLockMode.ReadWrite, image.PixelFormat);
BlobCounter blobCounter = new BlobCounter();
Invert invertfilter = new Invert();
invertfilter.ApplyInPlace(data);
blobCounter.ProcessImage(data);
Blob[] blobs = blobCounter.GetObjectsInformation();
if (blobs.Length != 0)
{
int maxar = 0;
int b = 0;
for (int i = 0; i < blobs.Count(); i++)
{
if (blobs[i].Area > maxar) { maxar = blobs[i].Area; b = i; }
}
invertfilter.ApplyInPlace(data);
System.Drawing.Point p = new System.Drawing.Point(_cells[0].CenterOfGravity.X - ((maxWidth / 2) - Convert.ToInt16(blobs[b].CenterOfGravity.X)), _cells[0].CenterOfGravity.Y - ((maxHeigth / 2) - Convert.ToInt16(blobs[b].CenterOfGravity.Y)));
if (Math.Abs(_cells[0].CenterOfGravity.Y - p.Y) <= maxslice) { this.ReMeasure(p, intercentresdistX, Width, Height); }
else { this.ReMeasure(_cells[0].CenterOfGravity, intercentresdistX, Width, Height); }
}
image.UnlockBits(data);
}
/// <summary>
/// Scans dominant color on image and returns it.
/// Crops rank part on image and analyzes suit part on image
/// </summary>
/// <param name="bmp">Bitmap to be scanned</param>
/// <returns>Returns 'B' for black , 'R' for red</returns>
private char ScanColor(Bitmap bmp)
{
char color = 'B';
//Crop rank part
Crop crop = new Crop(new Rectangle(0, bmp.Height / 2, bmp.Width, bmp.Height / 2));
bmp = crop.Apply(bmp);
Bitmap temp = commonSeq.Apply(bmp); //Apply filters
//Find suit blob on image
BlobCounter counter = new BlobCounter();
counter.ProcessImage(temp);
Blob[] blobs = counter.GetObjectsInformation();
if (blobs.Length > 0) //If blobs found
{
Blob max = blobs[0];
//Find blob whose size is biggest
foreach (Blob blob in blobs)
{
if (blob.Rectangle.Height > max.Rectangle.Height)
max = blob;
else if (blob.Rectangle.Height == max.Rectangle.Height)
max = blob.Rectangle.Width > max.Rectangle.Width ? blob : max;
}
QuadrilateralTransformation trans = new QuadrilateralTransformation();
trans.SourceQuadrilateral = PointsCloud.FindQuadrilateralCorners(counter.GetBlobsEdgePoints(max));
bmp = trans.Apply(bmp); //Extract suit
}
//Lock Bits for processing
BitmapData imageData = bmp.LockBits(new Rectangle(0, 0, bmp.Width, bmp.Height),
ImageLockMode.ReadOnly, bmp.PixelFormat);
int totalRed = 0;
int totalBlack = 0;
unsafe
{
//Count red and black pixels
try
{
UnmanagedImage img = new UnmanagedImage(imageData);
int height = img.Height;
int width = img.Width;
int pixelSize = (img.PixelFormat == PixelFormat.Format24bppRgb) ? 3 : 4;
byte* p = (byte*)img.ImageData.ToPointer();
// for each line
for (int y = 0; y < height; y++)
{
// for each pixel
for (int x = 0; x < width; x++, p += pixelSize)
{
int r = (int)p[RGB.R]; //Red pixel value
int g = (int)p[RGB.G]; //Green pixel value
int b = (int)p[RGB.B]; //Blue pixel value
if (r > g + b) //If red component is bigger then total of green and blue component
totalRed++; //then its red
if (r <= g + b && r < 50 && g < 50 && b < 50) //If all components less 50
totalBlack++; //then its black
}
}
}
finally
{
bmp.UnlockBits(imageData); //Unlock
}
}
if (totalRed > totalBlack) //If red is dominant
color = 'R'; //Set color as Red
return color;
}
/// <summary>
/// Scans rank of card and returns result.
/// For recognizing rank, counts suits on image
/// </summary>
/// <param name="cardImage">Card image to be scanned</param>
/// <returns>Rank of card</returns>
private Rank ScanRank(Bitmap cardImage)
{
Rank rank = Rank.NOT_RECOGNIZED;
int total = 0;
Bitmap temp = commonSeq.Apply(cardImage); //Apply filters on image
BlobCounter blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
//Filter blobs whose width or height less than 30 pixels
blobCounter.MinHeight = blobCounter.MinWidth = 30;
blobCounter.ProcessImage(temp);
total = blobCounter.GetObjectsInformation().Length; //Get total number of objects
rank = (Rank)total; //Convert it to Rank
return rank;
}
/// <summary>
/// Detects and recognizes cards from source image
/// </summary>
/// <param name="source">Source image to be scanned</param>
/// <returns>Recognized Cards</returns>
public List<Card> Recognize(Bitmap source)
{
List<Card> collection = new List<Card>();
Bitmap temp = source.Clone(source.PixelFormat) as Bitmap; //Clone image to keep original image
FiltersSequence seq = new FiltersSequence();
seq.Add(Grayscale.CommonAlgorithms.BT709); //First add grayScaling filter
seq.Add(new OtsuThreshold()); //Then add binarization(thresholding) filter
temp = seq.Apply(source); // Apply filters on source image
//Extract blobs from image whose size width and height larger than 150
BlobCounter extractor = new BlobCounter();
extractor.FilterBlobs = true;
extractor.MinWidth = extractor.MinHeight = 150;
extractor.MaxWidth = extractor.MaxHeight = 350;
extractor.ProcessImage(temp);
//Will be used transform(extract) cards on source image
QuadrilateralTransformation quadTransformer = new QuadrilateralTransformation();
//Will be used resize(scaling) cards
ResizeBilinear resizer = new ResizeBilinear(CardWidth, CardHeight);
foreach (Blob blob in extractor.GetObjectsInformation())
{
//Get Edge points of card
List<IntPoint> edgePoints = extractor.GetBlobsEdgePoints(blob);
//Calculate/Find corners of card on source image from edge points
List<IntPoint> corners = PointsCloud.FindQuadrilateralCorners(edgePoints);
quadTransformer.SourceQuadrilateral = corners; //Set corners for transforming card
quadTransformer.AutomaticSizeCalculaton = true;
Bitmap cardImg = quadTransformer.Apply(source); //Extract(transform) card image
if (cardImg.Width > cardImg.Height) //If card is positioned horizontally
{
WriteableBitmap wbmp=(WriteableBitmap)cardImg;
wbmp = wbmp.Rotate(90);
cardImg = (Bitmap)wbmp; //Rotate
}
cardImg = resizer.Apply(cardImg); //Normalize card size
Card card = new Card(cardImg, corners.ToArray()); //Create Card Object
char color = ScanColor(card.GetTopLeftPart()); //Scan color
bool faceCard = IsFaceCard(cardImg); //Determine type of card(face or not)
if (!faceCard)
{
card.Suit = ScanSuit(cardImg, color); //Scan Suit of non-face card
card.Rank = ScanRank(cardImg); //Scan Rank of non-face card
}
else
{
Bitmap topLeft = card.GetTopLeftPart();
seq = null;
seq = new FiltersSequence();
seq.Add(Grayscale.CommonAlgorithms.BT709);
seq.Add(new BradleyLocalThresholding());
topLeft = seq.Apply(topLeft);
BlobsFiltering bFilter = new BlobsFiltering(5, 5, 150, 150);
bFilter.ApplyInPlace(topLeft); //Filter blobs that can not be a suit
//topLeft.Save("topleft.bmp", ImageFormat.Bmp);
card.Suit = ScanFaceSuit(topLeft, color); //Scan suit of face card
card.Rank = ScanFaceRank(topLeft); //Scan rank of face card
}
collection.Add(card); //Add card to collection
}
return collection;
}
/// <summary>
/// Display little noise object on image
/// </summary>
/// <param name="fillColor">Color to fill noise bject</param>
/// <param name="threshold">Threshold for noise oblect area</param>
public Image DisplayNoise(Color fillColor, int threshold = 100)
{
Bitmap bitmapImage = new Bitmap(_digit);
BlobCounter bc = new BlobCounter(bitmapImage);
// specify sort order
bc.ObjectsOrder = ObjectsOrder.Size;
Blob[] blobs = bc.GetObjectsInformation();
SolidBrush redBrush = new SolidBrush(fillColor);
using (Graphics digit1Graph = Graphics.FromImage(bitmapImage))
{
foreach (Blob blob in blobs)
{
if (blob.Area < threshold)
digit1Graph.FillRectangle(redBrush, blob.Rectangle);
}
}
return bitmapImage;
}
private async Task<IList<Rect>> GetPlateRectanglesAsync(Bitmap image)
{
var rectanglePoints = await Task.Factory.StartNew(() =>
{
var blobCounter = new BlobCounter
{
FilterBlobs = true,
MinHeight = 5,
MinWidth = 5
};
blobCounter.ProcessImage(image);
var blobs = blobCounter.GetObjectsInformation();
var shapeChecker = new SimpleShapeChecker();
var rectPoints = new List<List<AForgePoint>>();
foreach (var blob in blobs)
{
List<IntPoint> cornerPoints;
var edgePoints = blobCounter.GetBlobsEdgePoints(blob);
var points = new List<AForgePoint>();
if (shapeChecker.IsQuadrilateral(edgePoints, out cornerPoints))
{
var polygonType = shapeChecker.CheckPolygonSubType(cornerPoints);
if (polygonType == PolygonSubType.Rectangle ||
polygonType == PolygonSubType.Parallelogram)
{
foreach (var point in cornerPoints)
{
points.Add(new AForgePoint(point.X, point.Y));
}
rectPoints.Add(points);
}
}
}
return rectPoints;
});
var rects = rectanglePoints.Select(points => GetRect(points)).ToList();
var images = new List<WriteableBitmap>();
var cadidatesRects = new List<Rect>();
foreach (var rect in rects)
{
var ratio = rect.Height / rect.Width;
if (ratio >= MinPlateRatio && ratio <= MaxPlateRatio)
{
cadidatesRects.Add(rect);
}
}
return cadidatesRects;
}
/// <summary>
/// Remove little noise object on binary image
/// </summary>
/// <param name="threshold">Threshold for noise oblect area</param>
public void RemoveNoise(int threshold = 100)
{
BlobCounter bc = new BlobCounter(new Bitmap(_digit));
// specify sort order
bc.ObjectsOrder = ObjectsOrder.Size;
Blob[] blobs = bc.GetObjectsInformation();
SolidBrush redBrush = new SolidBrush(Color.Black);
Bitmap tempBitmap = new Bitmap(_digit);
using (Graphics digitGraph = Graphics.FromImage(tempBitmap))
{
foreach (Blob blob in blobs)
{
if (blob.Area < threshold)
digitGraph.FillRectangle(redBrush, blob.Rectangle);
}
}
_digit = tempBitmap;
}
public static IEnumerable<MagicCard> DetectCardArt(Bitmap cameraBitmap)
{
var ret = new List<MagicCard>();
var filteredBitmap = Grayscale.CommonAlgorithms.BT709.Apply(cameraBitmap);
// edge filter
var edgeFilter = new SobelEdgeDetector();
edgeFilter.ApplyInPlace(filteredBitmap);
// Threshhold filter
var threshholdFilter = new Threshold(190);
threshholdFilter.ApplyInPlace(filteredBitmap);
var bitmapData = filteredBitmap.LockBits(
new Rectangle(0, 0, filteredBitmap.Width, filteredBitmap.Height),
ImageLockMode.ReadWrite, filteredBitmap.PixelFormat);
var blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
blobCounter.MinHeight = 125;
blobCounter.MinWidth = 125;
blobCounter.ProcessImage(bitmapData);
var blobs = blobCounter.GetObjectsInformation();
filteredBitmap.UnlockBits(bitmapData);
var shapeChecker = new SimpleShapeChecker();
var bm = new Bitmap(filteredBitmap.Width, filteredBitmap.Height, PixelFormat.Format24bppRgb);
var cardPositions = new List<IntPoint>();
foreach (var blob in blobs)
{
var edgePoints = blobCounter.GetBlobsEdgePoints(blob);
List<IntPoint> corners;
// only operate on 4 sided polygons
if (shapeChecker.IsConvexPolygon(edgePoints, out corners))
{
var subtype = shapeChecker.CheckPolygonSubType(corners);
if (corners.Count() != 4)
continue;
if (subtype != PolygonSubType.Parallelogram && subtype != PolygonSubType.Rectangle)
continue;
// if the image is sideways, rotate it so it'll match the DB card art
corners = Utilities.RotateCorners(corners).ToList();
if (Utilities.GetArea(corners) < 20000)
continue;
ret.Add( new MagicCard(cameraBitmap, corners));
}
}
return ret;
}
public bool markKnownForms()
{
if (currentImage != null)
{
try
{
Bitmap image = new Bitmap(this.currentImage);
// lock image
BitmapData bmData = image.LockBits(
new Rectangle(0, 0, image.Width, image.Height),
ImageLockMode.ReadWrite, image.PixelFormat);
// turn background to black
ColorFiltering cFilter = new ColorFiltering();
cFilter.Red = new IntRange(0, 64);
cFilter.Green = new IntRange(0, 64);
cFilter.Blue = new IntRange(0, 64);
cFilter.FillOutsideRange = false;
cFilter.ApplyInPlace(bmData);
// locate objects
BlobCounter bCounter = new BlobCounter();
bCounter.FilterBlobs = true;
bCounter.MinHeight = 5;
bCounter.MinWidth = 5;
bCounter.ProcessImage(bmData);
numberOfShellsDetected = bCounter.ObjectsCount;
Blob[] baBlobs = bCounter.GetObjectsInformation();
image.UnlockBits(bmData);
// coloring objects
SimpleShapeChecker shapeChecker = new SimpleShapeChecker();
Graphics g = Graphics.FromImage(image);
Pen yellowPen = new Pen(Color.Yellow, 2); // circles
Pen redPen = new Pen(Color.Red, 2); // quadrilateral
Pen brownPen = new Pen(Color.Brown, 2); // quadrilateral with known sub-type
Pen greenPen = new Pen(Color.Green, 2); // known triangle
Pen bluePen = new Pen(Color.Blue, 2); // triangle
for (int i = 0, n = baBlobs.Length; i < n; i++)
{
List<IntPoint> edgePoints = bCounter.GetBlobsEdgePoints(baBlobs[i]);
foreach (IntPoint point in edgePoints)
g.DrawEllipse(redPen, point.X, point.Y, 2, 2);
/*AForge.Point center;
float radius;
// is circle ?
if (shapeChecker.IsCircle(edgePoints, out center, out radius))
{
numberOfShellsDetected++;
g.DrawEllipse(redPen,
(float)(center.X - radius), (float)(center.Y - radius),
(float)(radius * 2), (float)(radius * 2));
}*/
/*else
{
List<IntPoint> corners;
// is triangle or quadrilateral
if (shapeChecker.IsConvexPolygon(edgePoints, out corners))
{
PolygonSubType subType = shapeChecker.CheckPolygonSubType(corners);
Pen pen;
if (subType == PolygonSubType.Unknown)
{
pen = (corners.Count == 4) ? redPen : bluePen;
}
else
{
pen = (corners.Count == 4) ? brownPen : greenPen;
}
g.DrawPolygon(pen, ToPointsArray(corners));
}
}*/
}
yellowPen.Dispose();
redPen.Dispose();
greenPen.Dispose();
bluePen.Dispose();
brownPen.Dispose();
g.Dispose();
this.currentImage = image;
return true;
}
catch (Exception e)
{
}
}
return false;
}
/// <summary>
/// Detect hand on a given frame
/// </summary>
/// <param name="image">Image to detect the hand palm within</param>
/// <param name="cycles">Number of snapshot cycles to check against</param>
/// <param name="similarityRate">The threshold percent of pixels that have to match for a positive result</param>
/// <param name="trainingPic">A reference to secondary frame field. Temporary.</param>
/// <returns>IntPoint point at the centre of detected hand palm</returns>
public IntPoint DetectHand(Bitmap image, int cycles, int similarityRate, PictureBox trainingPic)
{
IntPoint dimensions = new IntPoint(image.Width, image.Height);
BlobCounterBase bc = new BlobCounter();
Crop cropFilter;
bc.FilterBlobs = true;
bc.MinWidth = (int)(avgSize.x * 0.6);
bc.MinHeight = (int)(avgSize.y * 0.6);
bc.ObjectsOrder = ObjectsOrder.Size;
bc.ProcessImage(image);
Blob[] blobs = bc.GetObjectsInformation();
int blobWidth = 0;
int blobHeight = 0;
float blobAspectRatio;
double angle;
RotateBilinear rotate;
ResizeBilinear resize = new ResizeBilinear((int)avgSize.x, (int)avgSize.y);
Bitmap bmp;
List<IntPoint> edges = new List<IntPoint>();
for (int b = 0; b < blobs.Length; b++)
{
Rectangle br = blobs[b].Rectangle;
cropFilter = new Crop(br);
image = cropFilter.Apply(image);
bmp = AForge.Imaging.Image.Clone(image);
//bc.ExtractBlobsImage(image, blobs[b], false);
//bmp = new Bitmap(image.Width, image.Height, PixelFormat.Format24bppRgb);
edges = bc.GetBlobsEdgePoints(blobs[b]);
IntPoint circleCenter = FindLargestCircleCenter(edges, blobs[b].Rectangle);
//bmp = ImageFilters.Draw(bmp, edges);
//Highlight circle center
//Graphics gfx = Graphics.FromImage(bmp);
//gfx.DrawRectangle(new Pen(Color.Red, 3), circleCenter.X - 10, circleCenter.Y - 10, 20, 20);
blobWidth = blobs[b].Rectangle.Width;
blobHeight = blobs[b].Rectangle.Height;
blobAspectRatio = (float)blobWidth / blobHeight;
if((blobAspectRatio) > avgAspectRatio + 0.08)
{
float test3 = avgSize.y / avgSize.x;
if ((blobAspectRatio - avgAspectRatio) <= 1)
{
angle = ((blobAspectRatio - avgAspectRatio) / (test3 - avgAspectRatio)) * 90 + (1 - (blobAspectRatio - avgAspectRatio)) * 30;
}
else
{
angle = ((blobAspectRatio - avgAspectRatio) / (test3 - avgAspectRatio)) * 90;
}
rotate = new RotateBilinear(angle, false);
image = rotate.Apply(image);
//bmp = rotate.Apply(bmp);
}
image = resize.Apply(image);
//bmp = resize.Apply(bmp);
//image = cropFilter.Apply(image);
//image = maxBlobFilter.Apply(image);
int scannedPixels = 0;
int matches = 0;
float test = 0;
float threshold = (float)similarityRate / 100;
int imgHeight, imgWidth;
for (int i = 0; i < cycles; i++)
{
for (int smpl = 0; smpl < 10; smpl++)
{
if (image.Size.Width < samples[i, smpl].Size.Width)
imgWidth = image.Size.Width;
else
imgWidth = samples[i, smpl].Size.Width;
if (image.Size.Height < samples[i, smpl].Size.Height)
imgHeight = image.Size.Height;
else
imgHeight = samples[i, smpl].Size.Height;
for (int y = 0; y < imgHeight; y += 3)
for (int x = 0; x < imgWidth; x += 3)
{
scannedPixels++;
lock (samples[i, smpl])
{
lock (image)
{
if (image.GetPixel(x, y).Equals(samples[i, smpl].GetPixel(x, y)))
{
matches++;
}
}
}
}
test = (float)matches / (float)scannedPixels;
if (test >= threshold)
{
//bc.ExtractBlobsImage(image, blobs[b], false);
//bmp.Save("detect" + detectedNum + "o.bmp");
//image.Save("detect" + detectedNum + "r.bmp");
detectedNum++;
return new IntPoint(dimensions.X - circleCenter.X, circleCenter.Y);
//return new IntPoint(image.Width - (int)blobs[b].CenterOfGravity.X, (int)blobs[b].CenterOfGravity.Y);
}
matches = 0;
scannedPixels = 0;
}
}
}
return new IntPoint();
}
