public IEnumerable <Sperm> Discover(Bitmap image)
{
var classificator = new SpermClassificator();
var blobFinder = new BlobFinder(provider);
var blobs = blobFinder.FindBlobsByArea(image);
GrahamConvexHull grahamScan = new GrahamConvexHull();
foreach (var blob in blobs)
{
List <IntPoint> leftEdge = new List <IntPoint>();
List <IntPoint> rightEdge = new List <IntPoint>();
List <IntPoint> topEdge = new List <IntPoint>();
List <IntPoint> bottomEdge = new List <IntPoint>();
// collect edge points
blobFinder.BlobCounter.GetBlobsLeftAndRightEdges(blob, out leftEdge, out rightEdge);
blobFinder.BlobCounter.GetBlobsTopAndBottomEdges(blob, out topEdge, out bottomEdge);
// find convex hull
List <IntPoint> edgePoints = new List <IntPoint>();
edgePoints.AddRange(leftEdge);
edgePoints.AddRange(rightEdge);
List <IntPoint> hull = grahamScan.FindHull(edgePoints);
var points = hull.Select(x => new Point(x.X, x.Y)).ToList();
var center = new Point(blob.CenterOfGravity.X, blob.CenterOfGravity.Y);
blobFinder.BlobCounter.ExtractBlobsImage(image, blob, false);
var blobBitmap = blob.Image.ToManagedImage(true);
var spermType = classificator.Classify(blobBitmap);
yield return(new Sperm(points, center, spermType));
}
}
public void FindTest()
{
List<IntPoint> contour = new List<IntPoint>();
int max = 100;
for (int i = 0; i < max; i++)
add(contour, i, max);
for (int i = 0; i < max; i++)
add(contour, max, i);
for (int i = 0; i < max; i++)
add(contour, 0, i);
for (int i = 0; i < max / 2; i++)
add(contour, i, i);
for (int i = 0; i < max / 2; i++)
add(contour, i + max / 2, max / 2 - i);
PointsMarker marker = new PointsMarker(contour);
var bitmap = AForge.Imaging.Image.CreateGrayscaleImage(max + 1, max + 1);
bitmap = marker.Apply(bitmap);
// Accord.Controls.ImageBox.Show(bitmap);
GrahamConvexHull graham = new GrahamConvexHull();
List<IntPoint> hull = graham.FindHull(contour);
ConvexHullDefects hullDefects = new ConvexHullDefects(10);
List<ConvexityDefect> defects = hullDefects.FindDefects(contour, hull);
Assert.AreEqual(1, defects.Count);
Assert.AreEqual(99, defects[0].Depth);
}
private void convexHullBlov(Bitmap saus)
{
// http://www.aforgenet.com/framework/features/blobs_processing.html
Bitmap olahData = (Bitmap)saus.Clone();
BlobCounter blCount = new BlobCounter();
blCount.ProcessImage(saus);
Blob[] blobs = blCount.GetObjectsInformation();
GrahamConvexHull hullFinder = new GrahamConvexHull();
BitmapData data = olahData.LockBits(new Rectangle(0, 0, olahData.Width, olahData.Height), ImageLockMode.ReadWrite, olahData.PixelFormat);
foreach (Blob blob in blobs)
{
List <IntPoint> leftPoints, rightPoints;
List <IntPoint> edgePoints = new List <IntPoint>();
// get blob's edge points
blCount.GetBlobsLeftAndRightEdges(blob, out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
// blob's convex hull
List <IntPoint> hull = hullFinder.FindHull(edgePoints);
Drawing.Polygon(data, hull, Color.Red);
}
olahData.UnlockBits(data);
pictureBox2.Image = olahData;
}
// Set monochromeImage to display by the control
public int ScanImage(Bitmap monochromeImage)
{
this.hulls.Clear();
this.image = monochromeImage;
this.blobCounter.ProcessImage(this.image);
this.blobs = this.blobCounter.GetObjectsInformation();
var grahamScan = new GrahamConvexHull();
foreach (var blob in this.GetBlobs())
{
List <IntPoint> leftEdge;
List <IntPoint> rightEdge;
List <IntPoint> topEdge;
List <IntPoint> bottomEdge;
// collect edge points
this.blobCounter.GetBlobsLeftAndRightEdges(blob, out leftEdge, out rightEdge);
this.blobCounter.GetBlobsTopAndBottomEdges(blob, out topEdge, out bottomEdge);
// find convex hull
var edgePoints = new List <IntPoint>();
edgePoints.AddRange(leftEdge);
edgePoints.AddRange(rightEdge);
List <IntPoint> hull = grahamScan.FindHull(edgePoints);
this.hulls.Add(blob.ID, hull);
}
return(this.blobs.Length);
}
private List <IntPoint> FindCorners(Bitmap bitmap)
{
List <IntPoint> corners = new List <IntPoint>();
using (var clone = bitmap.Clone() as Bitmap)
{
new EuclideanColorFiltering(new AForge.Imaging.RGB((byte)Red, (byte)Green, (byte)Blue), Radius).ApplyInPlace(clone);
using (var grayscaledBitmap = Grayscale.CommonAlgorithms.BT709.Apply(clone))
{
//new Threshold(Threshold).ApplyInPlace(grayscaledBitmap);
if (Inverted)
{
new Invert().ApplyInPlace(grayscaledBitmap);
}
BlobCounter blobCounter = new BlobCounter();
blobCounter.FilterBlobs = true;
blobCounter.MinWidth = 50;
blobCounter.MinHeight = 50;
blobCounter.ObjectsOrder = ObjectsOrder.Size;
blobCounter.ProcessImage(grayscaledBitmap);
Blob[] blobs = blobCounter.GetObjectsInformation();
GrahamConvexHull hullFinder = new GrahamConvexHull();
for (int i = 0, n = blobs.Length; i < n; i++)
{
List <IntPoint> leftPoints, rightPoints;
List <IntPoint> edgePoints = new List <IntPoint>();
blobCounter.GetBlobsLeftAndRightEdges(blobs[i], out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
corners = hullFinder.FindHull(edgePoints);
}
}
}
return(corners);
}
public void FindHullTest()
{
var grahamHull = new GrahamConvexHull();
for (int i = 0, n = pointsLists.Count; i < n; i++)
{
ComparePointsLists(grahamHull.FindHull(pointsLists[i]), expectedHulls[i]);
}
}
/// <summary>
/// 분석 버튼 이벤트
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void btnAnalysis_Click(object sender, EventArgs e)
{
if (sqPoints.Count() <= 0)
{
transfer();
}
if (sqPoints.Count() > 2)
{
// Convex Hull 라이브러리
IConvexHullAlgorithm hullFinder = new GrahamConvexHull();
resultPoints = hullFinder.FindHull(sqPoints);
IntPoint[] ip = resultPoints.ToArray();
PointF[] pointf = new PointF[ip.Count <IntPoint>()];
for (int i = 0; i < ip.Length; i++)
{
pointf[i].X = ip[i].X;
pointf[i].Y = ip[i].Y;
}
for (int i = 0; i < resultPoints.Count; i++)
{
for (int j = 0; j < sqPoints.Count; j++)
{
if (sqPoints[j] == resultPoints[i])
{
listIndex.Add(j);
}
}
}
//Convex Hull 둘레 측정
double round = getRound(ip);
int x = panel1.Size.Width / 2;
int y = panel1.Size.Height / 2;
System.Drawing.Point p = new System.Drawing.Point(x, y);
lblRound.Location = p;
lblRound.Visible = true;
lblRound.Text = round.ToString("##.##");
foreach (int t in listIndex)
{
S3.Points.AddXY(cirPoints[t].X, cirPoints[t].Y);
}
S1.Points.Clear();
S2.Points.Clear();
S4.Points.Clear();
S3.Points.AddXY(cirPoints[listIndex[0]].X, cirPoints[listIndex[0]].Y);
}
else
{
MessageBox.Show("데이터가 부족합니다.", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
public void blobcounter_test()
{
string basePath = Path.Combine(NUnit.Framework.TestContext.CurrentContext.TestDirectory, "Resources");
#region doc_process
// Load an example image containing blobs (such the sample from the Blob Detection sample applications)
// https://github.com/accord-net/framework/raw/development/Samples/Imaging/Detection%20(Blobs)/demo.png
Bitmap image = Accord.Imaging.Image.FromFile(Path.Combine(basePath, "blob-input.png"));
// Creeate a new blob counter object
var blobCounter = new BlobCounter();
// Process the image looking for blobs
blobCounter.ProcessImage(image);
// Get information about all the image blobs found:
Blob[] blobs = blobCounter.GetObjectsInformation();
// Prepare to extract their Convex Hull
var grahamScan = new GrahamConvexHull();
var colors = new ColorSequenceCollection();
// For each blob in the image
for (int i = 0; i < blobs.Length; i++)
{
// Get the blob
Blob blob = blobs[i];
// Collect edge points
List <IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(blob);
// Find convex hull
List <IntPoint> hull = grahamScan.FindHull(edgePoints);
// Prepare to mark the hull in the image
var marker = new PointsMarker(colors[i])
{
Points = hull,
Connect = true // connect the points with line segments
};
// Draw the hull lines
marker.ApplyInPlace(image);
}
// Save the image to disk
image.Save(Path.Combine(basePath, "test.png"));
#endregion
Assert.AreEqual(25, blobs.Length);
}
private List <IntPoint> getHull(Blob blob, Bitmap grayImage)
{
GrahamConvexHull hullFinder = new GrahamConvexHull();
List <IntPoint> leftPoints, rightPoints, edgePoints = new List <IntPoint>();
BlobCounter blobCounter = getBlobCounter(grayImage);
// get blob's edge points
blobCounter.GetBlobsLeftAndRightEdges(blob,
out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
// blob's convex hull
return(hullFinder.FindHull(edgePoints));
}
public void FindTest()
{
List <IntPoint> contour = new List <IntPoint>();
int max = 100;
for (int i = 0; i < max; i++)
{
add(contour, i, max);
}
for (int i = 0; i < max; i++)
{
add(contour, max, i);
}
for (int i = 0; i < max; i++)
{
add(contour, 0, i);
}
for (int i = 0; i < max / 2; i++)
{
add(contour, i, i);
}
for (int i = 0; i < max / 2; i++)
{
add(contour, i + max / 2, max / 2 - i);
}
PointsMarker marker = new PointsMarker(contour);
var bitmap = AForge.Imaging.Image.CreateGrayscaleImage(max + 1, max + 1);
bitmap = marker.Apply(bitmap);
// ImageBox.Show(bitmap);
GrahamConvexHull graham = new GrahamConvexHull();
List <IntPoint> hull = graham.FindHull(contour);
ConvexHullDefects hullDefects = new ConvexHullDefects(10);
List <ConvexityDefect> defects = hullDefects.FindDefects(contour, hull);
Assert.AreEqual(1, defects.Count);
Assert.AreEqual(99, defects[0].Depth);
}
public List <IntPoint> FindConvexHull(double value)
{
var points = new List <IntPoint>();
for (int i = 0; i < ActualImageSize; i++)
{
for (int j = 0; j < ActualImageSize; j++)
{
if (_newTopo[i, j] < value)
{
points.Add(new IntPoint(i, j));
}
}
}
IConvexHullAlgorithm hullFinder = new GrahamConvexHull();
return(hullFinder.FindHull(points));
}
public void FindDefectsTest()
{
Bitmap bmp = Properties.Resources.hand;
Bitmap gray = AForge.Imaging.Filters.Grayscale.CommonAlgorithms.BT709.Apply(bmp);
BlobCounter bc = new BlobCounter(gray);
bc.ObjectsOrder = ObjectsOrder.Size;
Blob[] blobs = bc.GetObjectsInformation();
bc.ExtractBlobsImage(bmp, blobs[0], true);
Bitmap blob = blobs[0].Image.ToManagedImage();
BorderFollowing bf = new BorderFollowing();
List<IntPoint> contour = bf.FindContour(blob);
GrahamConvexHull graham = new GrahamConvexHull();
List<IntPoint> hull = graham.FindHull(contour);
ConvexHullDefects hullDefects = new ConvexHullDefects(10);
List<ConvexityDefect> defects = hullDefects.FindDefects(contour, hull);
/* PointsMarker marker = new PointsMarker(hull, Color.Green, 10);
marker.ApplyInPlace(blob);
ImageBox.Show(blob);
*/
Assert.AreEqual(2, defects.Count);
Assert.AreEqual(new IntPoint(130, 10), contour[defects[0].Start]);
Assert.AreEqual(new IntPoint(93, 109), contour[defects[0].Point]);
Assert.AreEqual(new IntPoint(64, 9), contour[defects[0].End]);
Assert.AreEqual(99.549179077148438, defects[0].Depth, 1e-5);
Assert.IsFalse(double.IsNaN(defects[0].Depth));
// Assert.AreEqual(9912.9531239366424, defects[0].Area);
Assert.AreEqual(new IntPoint(49, 18), contour[defects[1].Start]);
Assert.AreEqual(new IntPoint(61, 106), contour[defects[1].Point]);
Assert.AreEqual(new IntPoint(18, 127), contour[defects[1].End]);
Assert.AreEqual(35.615153852366504, defects[1].Depth, 1e-5);
Assert.IsFalse(double.IsNaN(defects[1].Depth));
// Assert.AreEqual(2293.7535682510002, defects[1].Area);
}
public void FindDefectsTest()
{
Bitmap bmp = Properties.Resources.hand;
Bitmap gray = AForge.Imaging.Filters.Grayscale.CommonAlgorithms.BT709.Apply(bmp);
BlobCounter bc = new BlobCounter(gray);
bc.ObjectsOrder = ObjectsOrder.Size;
Blob[] blobs = bc.GetObjectsInformation();
bc.ExtractBlobsImage(bmp, blobs[0], true);
Bitmap blob = blobs[0].Image.ToManagedImage();
BorderFollowing bf = new BorderFollowing();
List <IntPoint> contour = bf.FindContour(blob);
GrahamConvexHull graham = new GrahamConvexHull();
List <IntPoint> hull = graham.FindHull(contour);
ConvexHullDefects hullDefects = new ConvexHullDefects(10);
List <ConvexityDefect> defects = hullDefects.FindDefects(contour, hull);
/* PointsMarker marker = new PointsMarker(hull, Color.Green, 10);
* marker.ApplyInPlace(blob);
* ImageBox.Show(blob);
*/
Assert.AreEqual(2, defects.Count);
Assert.AreEqual(new IntPoint(130, 10), contour[defects[0].Start]);
Assert.AreEqual(new IntPoint(93, 109), contour[defects[0].Point]);
Assert.AreEqual(new IntPoint(64, 9), contour[defects[0].End]);
Assert.AreEqual(99.549179077148438, defects[0].Depth, 1e-5);
Assert.IsFalse(double.IsNaN(defects[0].Depth));
// Assert.AreEqual(9912.9531239366424, defects[0].Area);
Assert.AreEqual(new IntPoint(49, 18), contour[defects[1].Start]);
Assert.AreEqual(new IntPoint(61, 106), contour[defects[1].Point]);
Assert.AreEqual(new IntPoint(18, 127), contour[defects[1].End]);
Assert.AreEqual(35.615153852366504, defects[1].Depth, 1e-5);
Assert.IsFalse(double.IsNaN(defects[1].Depth));
// Assert.AreEqual(2293.7535682510002, defects[1].Area);
}
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);
}
// Set monochromeImage to display by the control
public IList <Polygon> ScanImage(Bitmap monochromeImage)
{
this.hulls.Clear();
this.image = monochromeImage;
this.blobCounter.ProcessImage(this.image);
this.blobs = this.blobCounter.GetObjectsInformation();
var grahamScan = new GrahamConvexHull();
var polygons = new List <Polygon>();
foreach (var blob in this.GetBlobs())
{
List <IntPoint> leftEdge;
List <IntPoint> rightEdge;
// collect edge points
this.blobCounter.GetBlobsLeftAndRightEdges(blob, out leftEdge, out rightEdge);
// find convex hull
var edgePoints = new List <IntPoint>();
edgePoints.AddRange(leftEdge);
edgePoints.AddRange(rightEdge);
var hull = grahamScan.FindHull(edgePoints);
this.hulls.Add(blob.ID, hull);
var minX = edgePoints.Min(x => x.X);
var minY = edgePoints.Min(x => x.Y);
var maxY = edgePoints.Max(x => x.Y);
var maxX = edgePoints.Max(x => x.X);
polygons.Add(new Polygon(new Point(minX, minY), new Point(maxX, maxY)));
}
return(polygons);
}
private void convexHull()
// Convex Hull
{
// Declare image
Bitmap bmp = new Bitmap(pictureBox1.Image);
// process image with blob counter
BlobCounter blobCounter = new BlobCounter();
blobCounter.ProcessImage(bmp);
Blob[] blobs = blobCounter.GetObjectsInformation();
// create convex hull searching algorithm
GrahamConvexHull hullFinder = new GrahamConvexHull();
// lock image to draw on it
BitmapData data = bmp.LockBits(
new Rectangle(0, 0, bmp.Width, bmp.Height),
ImageLockMode.ReadWrite, bmp.PixelFormat);
// process each blob
foreach (Blob blob in blobs)
{
List <IntPoint> leftPoints, rightPoints, edgePoints;
edgePoints = new List <IntPoint>();
// get blob's edge points
blobCounter.GetBlobsLeftAndRightEdges(blob,
out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
// blob's convex hull
List <IntPoint> hull = hullFinder.FindHull(edgePoints);
Drawing.Polygon(data, hull, Color.Red);
}
bmp.UnlockBits(data);
pictureBox1.Image = bmp;
}
private void button1_Click(object sender, EventArgs e)
{
pointNum = Convert.ToInt16(textBox1.Text);
Graphics graph = Graphics.FromImage(drawArea);
graph.Clear(Color.White);
List <IntPoint> list = new List <IntPoint>();
Random rand = new Random();
for (int i = 0; i < pointNum; i++)
{
list.Add(new IntPoint(
rand.Next(200),
rand.Next(200)
));
}
foreach (var point in list)
{
graph.FillEllipse(Brushes.Black, point.X, point.Y, 10, 10);
}
pictureBox1.Image = drawArea;
graph.Dispose();
IConvexHullAlgorithm hullFinder = new GrahamConvexHull();
List <IntPoint> hulls = hullFinder.FindHull(list);
Bitmap bmp = new Bitmap(drawArea);
Graphics graph2 = Graphics.FromImage(bmp);
Pen pen = new Pen(Color.Lime, 5);
for (int i = 0; i < hulls.Count - 1; i++)
{
graph2.DrawLine(pen, hulls.ElementAt(i).X, hulls.ElementAt(i).Y,
hulls.ElementAt(i + 1).X, hulls.ElementAt(i + 1).Y);
}
graph2.DrawLine(pen, hulls.ElementAt(0).X, hulls.ElementAt(0).Y,
hulls.ElementAt(hulls.Count - 1).X, hulls.ElementAt(hulls.Count - 1).Y);
pictureBox2.Image = bmp;
}
private void extractConvexHull()
{
GrahamConvexHull hullFinder = new GrahamConvexHull();
// process each blob
hulls = new List <Polygon>();
foreach (Blob blob in blobs)
{
List <IntPoint> leftPoints, rightPoints, edgePoints;
edgePoints = new List <IntPoint>();
// get blob's edge points
BlobCounter.GetBlobsLeftAndRightEdges(blob,
out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
// blob's convex hull
List <IntPoint> hull = hullFinder.FindHull(edgePoints);
hulls.Add(new Polygon(hull));
}
}
private void btn_search_Click(object sender, EventArgs e)
{
//bright = 0;
// value = 10;
openFileDialog1.Title = "영상파일 열기";
openFileDialog1.Filter = "All Files(*.*)|*.*| Bitmap File(*.bmp)|*.bmp|GIF File(*.gif)|*.gif|JPEG File(*.jpg)|*.jpg|PNG file(*.png)|*.png|TIFF(*.tif)|*.tif";
if (openFileDialog1.ShowDialog() == DialogResult.OK)
{
openstrFilename = openFileDialog1.FileName;
image = System.Drawing.Image.FromFile(openstrFilename);
myBitmap = new Bitmap(image);
this.xray_preview.Image = myBitmap;// 원 이미지를 담는 PictureBox 개체
}
//임시화일삭제
string filePath = @"Image\temp.jpg";
FileInfo file = new FileInfo(filePath);
if (file.Exists)
{
file.Delete();
}
/*
*손바닥 외곽선 추출
*/
Bitmap CroppedImage = myBitmap.Clone(new System.Drawing.Rectangle(0, 100, myBitmap.Width, (myBitmap.Height - 100)), myBitmap.PixelFormat); //손바닥
int width = 600;
int height = 600;
Size resize = new Size(width, height);
resizeImage = new Bitmap(CroppedImage, resize);
gsImage = Grayscale.CommonAlgorithms.BT709.Apply(resizeImage);
filter = new CannyEdgeDetector();
edge = filter.Apply(gsImage);
//외곽선 블러링
Blur hfilter = new Blur();
// apply the filter
hfilter.ApplyInPlace(edge);
///////////////////////////
// process image with blob counter
BlobCounter hblobCounter = new BlobCounter();
hblobCounter.ProcessImage(edge);
Blob[] hblobs = hblobCounter.GetObjectsInformation();
// create convex hull searching algorithm
GrahamConvexHull hhullFinder = new GrahamConvexHull();
// lock image to draw on it
BitmapData hdata = edge.LockBits(new Rectangle(0, 0, edge.Width, edge.Height), ImageLockMode.ReadWrite, edge.PixelFormat);
// process each blob
List <IntPoint> hhull = new List <IntPoint> {
};
List <IntPoint> hedgePoints = new List <IntPoint> {
};
int hblobcount = 0;
int hminX = 0, hmaxX = 700, hminY = 0, hmaxY = 700;
foreach (Blob blob in hblobs)
{
List <IntPoint> leftPoints, rightPoints;
// get blob's edge points
hblobCounter.GetBlobsLeftAndRightEdges(blob, out leftPoints, out rightPoints);
hedgePoints.AddRange(leftPoints);
hedgePoints.AddRange(rightPoints);
// blob's convex hull
hhull = hhullFinder.FindHull(hedgePoints);
foreach (IntPoint hulls in hhull)
{ // convexhull 최외곽선 추출
if (hblobcount == 0)
{
hminX = hulls.X; hmaxX = hulls.X;
hminY = hulls.Y; hmaxY = hulls.Y;
}
if (hminX > hulls.X)
{
hminX = hulls.X;
}
else if (hmaxX < hulls.X)
{
hmaxX = hulls.X;
}
if (hminY > hulls.Y)
{
hminY = hulls.Y;
}
else if (hmaxY < hulls.Y)
{
hmaxY = hulls.Y;
}
hblobcount++;
}
Drawing.Polygon(hdata, hhull, Color.White);
}
edge = edge.Clone(new Rectangle(hminX, hminY, hmaxX - hminX, hmaxY - hminY), myBitmap.PixelFormat);
this.xray_preview.Image = edge;
///////////////////////////////////
//수골 및 지골 분할 및 특징 추출
//손목 : 요골 및 척골 (2곳)
//손바닥 : 제1,3,5지 중수골 (3곳)
//손가락 : 제1,3,5지 기절골 및 말절골 (6곳)
//손가락 : 제3. 5지 중수골 (2곳)
///////////////////////////////
//요골 추출 및 인지 알고리즘
CroppedImage1 = myBitmap.Clone(new System.Drawing.Rectangle(270, 620, 250, 180), myBitmap.PixelFormat); //1. 요골
//이미지 사이즈 정규화 요골 크롭 이미지 250 X 180 -> 125 X 125
CroppedImage1 = CroppedImage1.Clone(new System.Drawing.Rectangle(10, 0, 230, 150), myBitmap.PixelFormat);
width = 125;
height = 125;
resize = new Size(width, height);
resizeImage = new Bitmap(CroppedImage1, resize);
//전처리 및 특징 추출 루틴
//DetectCorners(CroppedImage1);
gsImage = Grayscale.CommonAlgorithms.BT709.Apply(resizeImage);
filter = new CannyEdgeDetector();
edge = filter.Apply(gsImage);
//외곽선 블러링
Blur Bfilter = new Blur();
// apply the filter
Bfilter.ApplyInPlace(edge);
///////////////////////////
// process image with blob counter
BlobCounter blobCounter = new BlobCounter();
blobCounter.ProcessImage(edge);
Blob[] blobs = blobCounter.GetObjectsInformation();
// create convex hull searching algorithm
GrahamConvexHull hullFinder = new GrahamConvexHull();
// lock image to draw on it
BitmapData data = edge.LockBits(new Rectangle(0, 0, edge.Width, edge.Height), ImageLockMode.ReadWrite, edge.PixelFormat);
// process each blob
List <IntPoint> hull = new List <IntPoint> {
};
List <IntPoint> edgePoints = new List <IntPoint> {
};
int blobcount = 0;
int minX = 0, maxX = 125, minY = 0, maxY = 125;
foreach (Blob blob in blobs)
{
List <IntPoint> leftPoints, rightPoints;
// get blob's edge points
blobCounter.GetBlobsLeftAndRightEdges(blob, out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
// blob's convex hull
hull = hullFinder.FindHull(edgePoints);
foreach (IntPoint hulls in hull) // convexhull 최외곽선 추출
{
if (blobcount == 0)
{
minX = hulls.X; maxX = hulls.X;
minY = hulls.Y; maxY = hulls.Y;
}
if (minX > hulls.X)
{
minX = hulls.X;
}
else if (maxX < hulls.X)
{
maxX = hulls.X;
}
if (minY > hulls.Y)
{
minY = hulls.Y;
}
else if (maxY < hulls.Y)
{
maxY = hulls.Y;
}
blobcount++;
}
Drawing.Polygon(data, hull, Color.White);
}
edge = resizeImage.Clone(new System.Drawing.Rectangle(minX, minY, maxX - minX, maxY - minY), myBitmap.PixelFormat);
CroppedImage1.Save(@"Image\temp.jpg", ImageFormat.Jpeg);
this.pB_radius.Image = edge;
/////////////////////////////////////////////////////////////
////////////////////////
//척골
//////////////
CroppedImage2 = myBitmap.Clone(new System.Drawing.Rectangle(133, 620, 200, 180), myBitmap.PixelFormat); //2. 척골
//이미지 사이즈 정규화 요골 크롭 이미지 250 X 180 -> 125 X 125
CroppedImage2 = CroppedImage2.Clone(new System.Drawing.Rectangle(0, 20, 200, 150), myBitmap.PixelFormat);
width = 125;
height = 125;
resize = new Size(width, height);
resizeImage = new Bitmap(CroppedImage2, resize);
//전처리 및 특징 추출 루틴
//DetectCorners(CroppedImage1);
gsImage = Grayscale.CommonAlgorithms.BT709.Apply(resizeImage);
filter = new CannyEdgeDetector();
edge = filter.Apply(gsImage);
//외곽선 블러링
Bfilter = new Blur();
// apply the filter
Bfilter.ApplyInPlace(edge);
///////////////////////////
// process image with blob counter
blobCounter = new BlobCounter();
blobCounter.ProcessImage(edge);
blobs = blobCounter.GetObjectsInformation();
// create convex hull searching algorithm
hullFinder = new GrahamConvexHull();
// lock image to draw on it
BitmapData data1 = edge.LockBits(new Rectangle(0, 0, edge.Width, edge.Height), ImageLockMode.ReadWrite, edge.PixelFormat);
// process each blob
hull = new List <IntPoint> {
};
edgePoints = new List <IntPoint> {
};
blobcount = 0;
minX = 0; maxX = 125; minY = 0; maxY = 125;
foreach (Blob blob in blobs)
{
List <IntPoint> leftPoints, rightPoints;
// get blob's edge points
blobCounter.GetBlobsLeftAndRightEdges(blob, out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
// blob's convex hull
hull = hullFinder.FindHull(edgePoints);
foreach (IntPoint hulls in hull)
{ // convexhull 최외곽선 추출
if (blobcount == 0)
{
minX = hulls.X; maxX = hulls.X;
minY = hulls.Y; maxY = hulls.Y;
}
if (minX > hulls.X)
{
minX = hulls.X;
}
else if (maxX < hulls.X)
{
maxX = hulls.X;
}
if (minY > hulls.Y)
{
minY = hulls.Y;
}
else if (maxY < hulls.Y)
{
maxY = hulls.Y;
}
blobcount++;
}
Drawing.Polygon(data1, hull, Color.White);
}
Bitmap edge1 = resizeImage.Clone(new System.Drawing.Rectangle(minX, minY, (maxX - minX), (maxY - minY)), myBitmap.PixelFormat);
this.pB_ulna.Image = edge1;
///////////////////////////////////////
CroppedImage3 = myBitmap.Clone(new System.Drawing.Rectangle(390, 500, 180, 180), myBitmap.PixelFormat); //3. 제1지 중수골
resizeImage = new Bitmap(CroppedImage3, resize);
this.pB_Met1.Image = CroppedImage3;
CroppedImage4 = myBitmap.Clone(new System.Drawing.Rectangle(266, 266, 180, 180), myBitmap.PixelFormat); //4.제3지 기절골/중절골
resizeImage = new Bitmap(CroppedImage4, resize);
this.pB_Met3.Image = CroppedImage4;
CroppedImage5 = myBitmap.Clone(new System.Drawing.Rectangle(75, 335, 180, 180), myBitmap.PixelFormat); //5. 제5지 중수골/기절골
resizeImage = new Bitmap(CroppedImage5, resize);
this.pB_Met5.Image = CroppedImage5;
CroppedImage6 = myBitmap.Clone(new System.Drawing.Rectangle(534, 410, 180, 180), myBitmap.PixelFormat); //6. 제1지 기절골
resizeImage = new Bitmap(CroppedImage6, resize);
this.pB_Pph1.Image = CroppedImage6;
CroppedImage7 = myBitmap.Clone(new System.Drawing.Rectangle(266, 266, 180, 180), myBitmap.PixelFormat); //7. 제3지 기절골/중절골
resizeImage = new Bitmap(CroppedImage7, resize);
this.pB_Pph3.Image = CroppedImage7;
CroppedImage8 = myBitmap.Clone(new System.Drawing.Rectangle(75, 335, 180, 180), myBitmap.PixelFormat); //8. 제5지 중수골/기절골
resizeImage = new Bitmap(CroppedImage8, resize);
this.pB_Pph5.Image = CroppedImage8;
CroppedImage9 = myBitmap.Clone(new System.Drawing.Rectangle(260, 110, 180, 180), myBitmap.PixelFormat); //9. 제3자 중절골
resizeImage = new Bitmap(CroppedImage9, resize);
this.pB_Mph3.Image = CroppedImage9;
CroppedImage10 = myBitmap.Clone(new System.Drawing.Rectangle(0, 250, 180, 180), myBitmap.PixelFormat); //10. 제5지 중절골
resizeImage = new Bitmap(CroppedImage10, resize);
this.pB_Mph5.Image = CroppedImage10;
CroppedImage11 = myBitmap.Clone(new System.Drawing.Rectangle(620, 320, 180, 180), myBitmap.PixelFormat); //11. 제1지 말절골
resizeImage = new Bitmap(CroppedImage11, resize);
this.pB_Dph1.Image = CroppedImage11;
CroppedImage12 = myBitmap.Clone(new System.Drawing.Rectangle(260, 0, 180, 180), myBitmap.PixelFormat); //12. 제3지 말절골
resizeImage = new Bitmap(CroppedImage12, resize);
this.pB_Dph3.Image = CroppedImage12;
CroppedImage13 = myBitmap.Clone(new System.Drawing.Rectangle(0, 133, 180, 180), myBitmap.PixelFormat); //13. 제5지 말절골
resizeImage = new Bitmap(CroppedImage13, resize);
this.pB_Dph5.Image = CroppedImage13;
//edge.UnlockBits(data1);
//edge.UnlockBits(data);
}
static void Main(string[] args)
{
Threshold thresh = new Threshold(10);
Median median = new Median(9);
Erosion3x3 erode = new Erosion3x3();
Dilatation3x3 dilate = new Dilatation3x3();
GrahamConvexHull hullFinder = new GrahamConvexHull();
ConnectedComponentsLabeling ccLabeler = new ConnectedComponentsLabeling();
BorderFollowing contourFinder = new BorderFollowing();
GrayscaleToRGB rgb = new GrayscaleToRGB();
ConvexHullDefects defectFinder = new ConvexHullDefects(10);
Bitmap img = (Bitmap)Bitmap.FromFile("hand3.jpg");
Bitmap image = Grayscale.CommonAlgorithms.BT709.Apply(img);
thresh.ApplyInPlace(image);
//median.ApplyInPlace(image);
erode.ApplyInPlace(image);
dilate.ApplyInPlace(image);
BlobCounter counter = new BlobCounter(image);
counter.ObjectsOrder = ObjectsOrder.Area;
Blob[] blobs = counter.GetObjectsInformation();
if (blobs.Length > 0)
{
counter.ExtractBlobsImage(image, blobs[0], true);
UnmanagedImage hand = blobs[0].Image;
var contour = contourFinder.FindContour(hand);
if (contour.Count() > 0)
{
var initialHull = hullFinder.FindHull(contour);
var defects = defectFinder.FindDefects(contour, initialHull);
var filteredHull = initialHull.ClusterHullPoints().FilterLinearHullPoints();
var palmCenter = defects.Centroid(contour);
var wristPoints = filteredHull.SelectWristPoints(defects, contour);
Bitmap color = rgb.Apply(hand).ToManagedImage();
//BitmapData data = color.LockBits(new Rectangle(0, 0, color.Width, color.Height), ImageLockMode.ReadWrite, color.PixelFormat);
//Drawing.Polyline(data, contour, Color.Blue);
//Drawing.Polygon(data, filteredHull, Color.Red);
//color.UnlockBits(data);
Graphics gr = Graphics.FromImage(color);
gr.DrawPolygon(new Pen(Brushes.Red, 3), filteredHull.ToPtArray());
gr.DrawLines(new Pen(Brushes.Blue, 3), contour.ToPtArray());
gr.DrawEllipse(new Pen(Brushes.Red, 3), palmCenter.X - 10, palmCenter.Y - 10, 20, 20);
foreach (ConvexityDefect defect in defects)
{
gr.DrawEllipse(new Pen(Brushes.Green, 6), contour[defect.Point].X - 10, contour[defect.Point].Y - 10, 20, 20);
}
foreach (AForge.IntPoint pt in filteredHull)
{
gr.DrawEllipse(new Pen(Brushes.Yellow, 6), pt.X - 10, pt.Y - 10, 20, 20);
}
foreach (AForge.IntPoint pt in wristPoints)
{
gr.DrawEllipse(new Pen(Brushes.PowderBlue, 6), pt.X - 10, pt.Y - 10, 20, 20);
}
ImageBox.Show(color);
}
}
}
private void process_Click(object sender, EventArgs e)
{
//grayscale
Grayscale filter1 = new Grayscale(0.2125, 0.7154, 0.0721);
processed = filter1.Apply(processed);
//threshold
var filter2 = new AForge.Imaging.Filters.Threshold(175);
processed = filter2.Apply(processed);
// erosion
Erosion filter3 = new Erosion();
filter3.Apply(processed);
// create filter
BlobsFiltering filter = new BlobsFiltering();
// configure filter
filter.CoupledSizeFiltering = true;
filter.MinWidth = 25;
filter.MinHeight = 25;
// apply the filter
filter.ApplyInPlace(processed);
Invert filterInvert = new Invert();
// apply the filter
filterInvert.ApplyInPlace(processed);
BlobCounterBase bc = new BlobCounter();
bc.FilterBlobs = true;
bc.MinWidth = 30; //give required value or ignore
bc.MinHeight = 30; //give required value or ignore
bc.CoupledSizeFiltering = true; // if value are given and if you want both Width and Height to be applied as a constraint to identify blob, set it to true
bc.ProcessImage(processed);
Blob[] blobs = bc.GetObjectsInformation();
int count = bc.ObjectsCount;
// lock image to draw on it
BitmapData data = processed.LockBits(
new Rectangle(0, 0, processed.Width, processed.Height),
ImageLockMode.ReadWrite, processed.PixelFormat);
// process each blob
foreach (Blob blob in blobs)
{
List <IntPoint> leftPoints, rightPoints, edgePoints;
edgePoints = new List <IntPoint>();
// get blob's edge points
bc.GetBlobsLeftAndRightEdges(blob,
out leftPoints, out rightPoints);
edgePoints.AddRange(leftPoints);
edgePoints.AddRange(rightPoints);
IConvexHullAlgorithm hullFinder = new GrahamConvexHull();
// blob's convex hull
List <IntPoint> hull = hullFinder.FindHull(edgePoints);
Drawing.Polygon(data, hull, Color.Yellow);
if (blob.Area < 8000)
{
five_cents++;
}
else if (blob.Area < 9000 && blob.Area > 8000)
{
ten_cents++;
}
else if (blob.Area < 13000 && blob.Area > 11000)
{
twentyfive_cents++;
}
else if (blob.Area < 17000 && blob.Area > 16000)
{
one_peso++;
}
else
{
five_peso++;
}
}
processed.UnlockBits(data);
pictureBox2.Image = processed;
pictureBox2.SizeMode = PictureBoxSizeMode.StretchImage;
textBox1.Text += count;
textBox2.Text += ((five_cents * .05) + (ten_cents * .10) + (twentyfive_cents * .25) + (one_peso * 1) + (five_peso * 5));
}
private void PatternRecognition(Bitmap bitmap) {
// Prvi korak - grayscalling originalne slike
Bitmap frame = grayscaleFilter.Apply(bitmap);
BitmapData frameData = frame.LockBits(new Rectangle(0, 0, frame.Width, frame.Height), ImageLockMode.ReadWrite, frame.PixelFormat);
// Drugi korak - detekcija ivica pomocu Sobel filtra
sobelFilter.ApplyInPlace(frameData);
// Treći korak - konvertuj sliku u crno-bijelu pri čemu je threshold = 100 odnoso od 0 do 155 je crna boja, a od 156 do 255 je bijela boja
thresholdFilter.ApplyInPlace(frameData);
// Četvrti korak - dilitacija / pojacavanje bijele boje jer
dilitationFilter.ApplyInPlace(frameData);
// Peti korak - kreiranje binarne slike
frame = frame.Clone(new Rectangle(0, 0, frame.Width, frame.Height), PixelFormat.Format8bppIndexed);
// Šesti korak - pronalazak potencijalnih oblika na slici
blobCounter.ProcessImage(frameData);
Blob[] blobs = blobCounter.GetObjectsInformation();
// za crtanje po originalnoj slici
Graphics g = Graphics.FromImage(bitmap);
// Sedmi korak - provjeri svaki oblik
foreach (Blob blob in blobs) {
List<IntPoint> edgePoints = blobCounter.GetBlobsEdgePoints(blob);
List<IntPoint> hullPoints = hullFinder.FindHull(edgePoints);
List<IntPoint> corners = null;
// da li je četverougao?
if (shapeChecker.IsQuadrilateral(hullPoints, out corners))
// da li je kvadrat?
if (shapeChecker.CheckPolygonSubType(corners) == PolygonSubType.Square) {
if (!detected) {
// Osmi korak - odrđivanje centra gravitacije i gornjeg lijevog tjemena
FindNewCorners(corners);
// Deveti korak - ekstrakcija prepoznatog kvadrata sa originalne slike u novu sliku dimenzija 100x100
SimpleQuadrilateralTransformation quadrilateralTransformation = new SimpleQuadrilateralTransformation(corners, 100, 100);
Bitmap recognizedSquare = quadrilateralTransformation.Apply(bitmap);
recognizedSquare = recognizedSquare.Clone(new Rectangle(0, 0, recognizedSquare.Width, recognizedSquare.Height), PixelFormat.Format8bppIndexed);
// Deseti korak - od nove slike ponovo napravi crno-bijelu
otsuThresholdFilter.ApplyInPlace(recognizedSquare);
// Jedanaesti korak - invertuj boje
invertFilter.ApplyInPlace(recognizedSquare);
//Dvanaesti korak - prepoznaj oblik (formiraj matricu)
float confidence; // vjerovatnoća da je prepoznat pravi oblik (odnos borja crnih i bijelih piksela u ćeliji
byte[,] pattern = binaryGlyphRecognizer.Recognize(recognizedSquare, new Rectangle(0, 0, recognizedSquare.Width, recognizedSquare.Height), out confidence);
recognizedSquare.Dispose();
if (confidence >= 0.6) {
oldPatterns.Add(pattern);
Boolean canDraw = CheckPrevious();
if (canDraw) {
// Trinaesti korak - iscrtaj matricu
DrawPattern(pattern);
detected = true;
// pravim delay od 3s nakon što prepozna pattern
new Task(() => {
Thread.Sleep(3*1000);
detected = false;
}).Start();
// Komunikacija sa warehouse uređajem.
//new Thread(new RS232Communication(shape).Run).Start();
}
}
}
// iscrtaj ivice oko prepoznatog kvadrata
g.DrawPolygon(pen, ToPointsArray(hullPoints));
}
}
g.Dispose();
frame.UnlockBits(frameData);
frame.Dispose();
}
/// <summary>
/// Detect Blobs in the bitmap image
/// </summary>
/// <param name="inputImage">Input bitmap image (Gray or RGB)</param>
/// <param name="minFullness"> 0 if you don't want a fullness filter</param>
/// <param name="maxNumOfFilteredBlobs"> How many filtered blob do you want be save in blobs_filter list</param>
///
/// <returns></returns>
public Blob_Aforge(Bitmap inputImage, int minWidth, int maxWidth, int minHeight, int maxHeight, double minFullness, int maxNumOfFilteredBlobs)
{
try
{
leftEdges.Clear();
rightEdges.Clear();
topEdges.Clear();
bottomEdges.Clear();
hulls.Clear();
//quadrilaterals.Clear();
///Get Image
this.image = AForge.Imaging.Image.Clone(inputImage, PixelFormat.Format24bppRgb);//
_imageWidth = this.image.Width;
_imageHeight = this.image.Height;
///Size Filter
blobCounter.FilterBlobs = true;
blobCounter.MinHeight = minHeight;
blobCounter.MinWidth = minWidth;
blobCounter.MaxHeight = maxHeight;
blobCounter.MaxWidth = maxWidth;
blobCounter.ObjectsOrder = ObjectsOrder.Area;
///Detection
///
blobCounter.ProcessImage(this.image);
blobs_all = blobCounter.GetObjectsInformation();
GrahamConvexHull grahamScan = new GrahamConvexHull();
foreach (Blob blob in blobs_all)
{
fullness = blob.Fullness;
if (fullness > minFullness & blobs_Filtered.Count < maxNumOfFilteredBlobs)///Fullness Filter
{
List <IntPoint> leftEdge = new List <IntPoint>();
List <IntPoint> rightEdge = new List <IntPoint>();
// List<IntPoint> topEdge = new List<IntPoint>();
// List<IntPoint> bottomEdge = new List<IntPoint>();
// collect edge points
blobCounter.GetBlobsLeftAndRightEdges(blob, out leftEdge, out rightEdge);
// blobCounter.GetBlobsTopAndBottomEdges(blob, out topEdge, out bottomEdge);
leftEdges.Add(blob.ID, leftEdge);
rightEdges.Add(blob.ID, rightEdge);
// topEdges.Add(blob.ID, topEdge);
// bottomEdges.Add(blob.ID, bottomEdge);
// find convex hull
List <IntPoint> edgePoints = new List <IntPoint>();
edgePoints.AddRange(leftEdge);
edgePoints.AddRange(rightEdge);
shapeChecker.MinAcceptableDistortion = (float)0.5;
shapeChecker.RelativeDistortionLimit = (float)0.15;
if (shapeChecker.IsCircle(edgePoints))
{
blobs_Filtered.Add(blob);
List <IntPoint> hull = grahamScan.FindHull(edgePoints);
hulls.Add(blobs_Filtered.Count - 1, hull);//sinchronized with blobs_filtered items
}
}
}
DrawBlobImage();
}
catch (Exception error)
{
//System.Windows.Forms.MessageBox.Show(error.ToString());
// METState.Current.ErrorSound.Play();
}
}
static void Main(string[] args)
{
Threshold thresh = new Threshold(10);
Median median = new Median(9);
Erosion3x3 erode = new Erosion3x3();
Dilatation3x3 dilate = new Dilatation3x3();
GrahamConvexHull hullFinder = new GrahamConvexHull();
ConnectedComponentsLabeling ccLabeler = new ConnectedComponentsLabeling();
BorderFollowing contourFinder = new BorderFollowing();
GrayscaleToRGB rgb = new GrayscaleToRGB();
ConvexHullDefects defectFinder = new ConvexHullDefects(10);
Bitmap img = (Bitmap)Bitmap.FromFile("hand3.jpg");
Bitmap image = Grayscale.CommonAlgorithms.BT709.Apply(img);
thresh.ApplyInPlace(image);
//median.ApplyInPlace(image);
erode.ApplyInPlace(image);
dilate.ApplyInPlace(image);
BlobCounter counter = new BlobCounter(image);
counter.ObjectsOrder = ObjectsOrder.Area;
Blob[] blobs = counter.GetObjectsInformation();
if (blobs.Length > 0)
{
counter.ExtractBlobsImage(image, blobs[0], true);
UnmanagedImage hand = blobs[0].Image;
var contour = contourFinder.FindContour(hand);
if (contour.Count() > 0)
{
var initialHull = hullFinder.FindHull(contour);
var defects = defectFinder.FindDefects(contour, initialHull);
var filteredHull = initialHull.ClusterHullPoints().FilterLinearHullPoints();
var palmCenter = defects.Centroid(contour);
var wristPoints = filteredHull.SelectWristPoints(defects, contour);
Bitmap color = rgb.Apply(hand).ToManagedImage();
//BitmapData data = color.LockBits(new Rectangle(0, 0, color.Width, color.Height), ImageLockMode.ReadWrite, color.PixelFormat);
//Drawing.Polyline(data, contour, Color.Blue);
//Drawing.Polygon(data, filteredHull, Color.Red);
//color.UnlockBits(data);
Graphics gr = Graphics.FromImage(color);
gr.DrawPolygon(new Pen(Brushes.Red, 3), filteredHull.ToPtArray());
gr.DrawLines(new Pen(Brushes.Blue, 3), contour.ToPtArray());
gr.DrawEllipse(new Pen(Brushes.Red, 3), palmCenter.X - 10, palmCenter.Y - 10, 20, 20);
foreach (ConvexityDefect defect in defects)
{
gr.DrawEllipse(new Pen(Brushes.Green, 6), contour[defect.Point].X - 10, contour[defect.Point].Y - 10, 20, 20);
}
foreach (AForge.IntPoint pt in filteredHull)
{
gr.DrawEllipse(new Pen(Brushes.Yellow, 6), pt.X - 10, pt.Y - 10, 20, 20);
}
foreach (AForge.IntPoint pt in wristPoints)
{
gr.DrawEllipse(new Pen(Brushes.PowderBlue, 6), pt.X - 10, pt.Y - 10, 20, 20);
}
ImageBox.Show(color);
}
}
}
public int SetImage(Bitmap image)
{
leftEdges.Clear();
rightEdges.Clear();
topEdges.Clear();
bottomEdges.Clear();
hulls.Clear();
quadrilaterals.Clear();
selectedBlobID = 0;
Bitmap imageclone = AForge.Imaging.Image.Clone(image, image.PixelFormat);
// create filter
Median filterMedian = new Median();
// apply the filter
// create filter
Threshold filterThreshold = new Threshold(250);
// configure filter
// create filter
BlobsFiltering filterBlobsFiltering = new BlobsFiltering();
filterBlobsFiltering.CoupledSizeFiltering = false;
filterBlobsFiltering.MinWidth = 6; //7
filterBlobsFiltering.MinHeight = 6; //7
filterBlobsFiltering.MaxWidth = 8; //8
filterBlobsFiltering.MaxHeight = 8; //8
// apply the filter
filterThreshold.ApplyInPlace(imageclone);
filterBlobsFiltering.ApplyInPlace(imageclone);
filterMedian.ApplyInPlace(imageclone);
//this.image = AForge.Imaging.Image.Clone( image, PixelFormat.Format16bppGrayScale );
//imageclone = AForge.Imaging.Image.Clone(image);
imageWidth = imageclone.Width;
imageHeight = imageclone.Height;
blobCounter.ProcessImage(imageclone);
blobs = blobCounter.GetObjectsInformation();
center = new List <AForge.Point>();
GrahamConvexHull grahamScan = new GrahamConvexHull();
foreach (Blob blob in blobs)
{
List <IntPoint> leftEdge = new List <IntPoint>();
List <IntPoint> rightEdge = new List <IntPoint>();
List <IntPoint> topEdge = new List <IntPoint>();
List <IntPoint> bottomEdge = new List <IntPoint>();
// collect edge points
blobCounter.GetBlobsLeftAndRightEdges(blob, out leftEdge, out rightEdge);
blobCounter.GetBlobsTopAndBottomEdges(blob, out topEdge, out bottomEdge);
AForge.Point centering = blob.CenterOfGravity;
leftEdges.Add(blob.ID, leftEdge);
rightEdges.Add(blob.ID, rightEdge);
topEdges.Add(blob.ID, topEdge);
bottomEdges.Add(blob.ID, bottomEdge);
// find convex hull
List <IntPoint> edgePoints = new List <IntPoint>();
edgePoints.AddRange(leftEdge);
edgePoints.AddRange(rightEdge);
List <IntPoint> hull = grahamScan.FindHull(edgePoints);
hulls.Add(blob.ID, hull);
List <IntPoint> quadrilateral = null;
// List array center of gravity
center.Add(centering);
// find quadrilateral //
if (hull.Count < 4)
{
quadrilateral = new List <IntPoint>(hull);
}
else
{
quadrilateral = PointsCloud.FindQuadrilateralCorners(hull);
}
quadrilaterals.Add(blob.ID, quadrilateral);
// shift all points for vizualization
IntPoint shift = new IntPoint(1, 1);
PointsCloud.Shift(leftEdge, shift);
PointsCloud.Shift(rightEdge, shift);
PointsCloud.Shift(topEdge, shift);
PointsCloud.Shift(bottomEdge, shift);
PointsCloud.Shift(hull, shift);
PointsCloud.Shift(quadrilateral, shift);
}
double xhair = imageWidth / 2;
double yhair = imageHeight / 2;
if (image.PixelFormat != PixelFormat.Format24bppRgb)
{
//filterBlobX(516.0, 670.0);
//filterBlobY(360.0, 520.0);
filterBlobX(516.0, 1117.0);
filterBlobY(357.0, 460.0);
refPointList = new List <AForge.Point>();
//findRef(388.0, 0.5);
findRef(20.0, 1.5);//
findPick(refPoint.X, refPoint.Y);
}
//UpdatePosition();
//Invalidate();
//if (!Directory.Exists(path))
//{
// System.IO.Directory.CreateDirectory(path);
//}
////file = path + DateTime.Now.ToString(datePatt);
file = path + "visimg.bmp";
imageclone.Save(file);
if (blobs.Length > 0)
{
return(blobs.Length);
}
else
{
return(0);
}
}
// Set image to display by the control
public int SetImage(Bitmap image)
{
leftEdges.Clear();
rightEdges.Clear();
topEdges.Clear();
bottomEdges.Clear();
hulls.Clear();
quadrilaterals.Clear();
selectedBlobID = 0;
this.image = Accord.Imaging.Image.Clone(image, PixelFormat.Format24bppRgb);
imageWidth = this.image.Width;
imageHeight = this.image.Height;
blobCounter.ProcessImage(this.image);
blobs = blobCounter.GetObjectsInformation();
GrahamConvexHull grahamScan = new GrahamConvexHull();
foreach (Blob blob in blobs)
{
List<IntPoint> leftEdge = new List<IntPoint>();
List<IntPoint> rightEdge = new List<IntPoint>();
List<IntPoint> topEdge = new List<IntPoint>();
List<IntPoint> bottomEdge = new List<IntPoint>();
// collect edge points
blobCounter.GetBlobsLeftAndRightEdges(blob, out leftEdge, out rightEdge);
blobCounter.GetBlobsTopAndBottomEdges(blob, out topEdge, out bottomEdge);
leftEdges.Add(blob.ID, leftEdge);
rightEdges.Add(blob.ID, rightEdge);
topEdges.Add(blob.ID, topEdge);
bottomEdges.Add(blob.ID, bottomEdge);
// find convex hull
List<IntPoint> edgePoints = new List<IntPoint>();
edgePoints.AddRange(leftEdge);
edgePoints.AddRange(rightEdge);
List<IntPoint> hull = grahamScan.FindHull(edgePoints);
hulls.Add(blob.ID, hull);
List<IntPoint> quadrilateral = null;
// find quadrilateral
if (hull.Count < 4)
{
quadrilateral = new List<IntPoint>(hull);
}
else
{
quadrilateral = PointsCloud.FindQuadrilateralCorners(hull);
}
quadrilaterals.Add(blob.ID, quadrilateral);
// shift all points for vizualization
IntPoint shift = new IntPoint(1, 1);
PointsCloud.Shift(leftEdge, shift);
PointsCloud.Shift(rightEdge, shift);
PointsCloud.Shift(topEdge, shift);
PointsCloud.Shift(bottomEdge, shift);
PointsCloud.Shift(hull, shift);
PointsCloud.Shift(quadrilateral, shift);
}
UpdatePosition();
Invalidate();
return blobs.Length;
}
public static List <Shapes.Component> FindComponents(VideoProcessing vp, 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
Point LongestCenter = new 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);
Point NormalStart = new Point();
Point NormalEnd = new 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)
Point InterSection = new Point();
Point Furthest = new 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 = (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
Point fPoint = new 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);
}
}
}
Point ComponentCenter = new 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));
}
}
SetVideoProcessing(Components, vp);
return(Components);
}