//座標算出
void SendLEDPtData(ref UDP_PACKETS_CODER.UDP_PACKETS_ENCODER enc)
{
CameraSpacePoint LEDPt = this.calib.GetLEDPositinon(this.imageWidth,
this.imageHeigt,
this.colors,
new OpenCvSharp.CPlusPlus.Scalar(30, 93, 93),
this.depthBuffer);
this.calib.MakeSaveData(this.calibMode, LEDPt);
enc += LEDPt.X;
enc += LEDPt.Y;
enc += LEDPt.Z;
Console.WriteLine("X:" + LEDPt.X.ToString());
Console.WriteLine("Y:" + LEDPt.Y.ToString());
Console.WriteLine("Z:" + LEDPt.Z.ToString());
//キャリブレーション画像表示
OpenCvSharp.CPlusPlus.Mat calibMat = calib.GetCalibrationImage().Clone();
this.calibrationImage.Source = OpenCvSharp.Extensions.WriteableBitmapConverter.ToWriteableBitmap(calibMat);
this.CalibrationImageTable.IsSelected = true;
//送信データ表示
this.message.Content = "LEDPosition " + "X:" + LEDPt.X.ToString() + " Y:" + LEDPt.Y.ToString() + " Z:" + LEDPt.Z.ToString();
//データ送信モード変更
this.SendData_LEDPt.IsChecked = false;
this.SendData_Body.IsChecked = true;
}
public void GetHsv(IplImage src)
{
IplImage hsv = new IplImage(WIDTH, HEIGHT, BitDepth.U8, 3);
//RGBからHSVに変換
Cv.CvtColor(src, hsv, ColorConversion.BgrToHsv);
OpenCvSharp.CPlusPlus.Mat mat = new OpenCvSharp.CPlusPlus.Mat(hsv, true);
int matw = mat.Width;
int math = mat.Height;
var re = mat.At <OpenCvSharp.CPlusPlus.Vec3b>(PointY, PointX);
Hdata = re[0];
Sdata = re[1];
Vdata = re[2];
}
private void CheckColor()
{
IplImage source = new IplImage(640, 360, BitDepth.U8, 3);
const int TEST_FRAME = 36;
var ListH = new List <int>();
int side = (int)Math.Sqrt(TEST_FRAME);//検査枠の１辺の長さ
try
{
Task.Run(() =>
{
while (FlagCheckCol)
{
try
{
//画像を取得する処理
if (!General.camLed.GetPic())
{
continue;
}
source = General.camLed.imageForTest;
using (var hsv = new IplImage(640, 360, BitDepth.U8, 3)) // グレースケール画像格納用の変数
{
//RGBからHSVに変換
Cv.CvtColor(source, hsv, ColorConversion.BgrToHsv);
OpenCvSharp.CPlusPlus.Mat mat = new OpenCvSharp.CPlusPlus.Mat(hsv, true);
TestpointForGetLum = GetTestPoint();
TestpointForGetLum.ForEach(l =>
{
ListH.Clear();
foreach (var i in Enumerable.Range(0, side))
{
foreach (var j in Enumerable.Range(0, side))
{
var re = mat.At <OpenCvSharp.CPlusPlus.Vec3b>(l.Item1.Y - (side / 2) + i, l.Item1.X - (side / 2) + j);
if (re[0] != 0)
{
ListH.Add(re[0]);
}
}
}
string Hue = (ListH.Count != 0) ? ListH.Average().ToString("F0") : "0";
switch (l.Item2)
{
case SEG_NAME.LED1:
State.VmLedPoint.LED1Hue = Hue;
break;
case SEG_NAME.LED2:
State.VmLedPoint.LED2Hue = Hue;
break;
case SEG_NAME.LED3:
State.VmLedPoint.LED3Hue = Hue;
break;
case SEG_NAME.LED4:
State.VmLedPoint.LED4Hue = Hue;
break;
}
});
}
}
catch
{
FlagCheckCol = false;
}
}
});
}
finally
{
source.Dispose();
}
}
public static void CheckLed()//引数には点灯するLEDを指定する
{
InitList();
State.SetCamProp();
General.cam.ResetFlag(); //カメラのフラグを初期化 リトライ時にフラグが初期化できてないとだめ
//例 ＮＧリトライ時は、General.cam.FlagFrame = trueになっていてNGフレーム表示の無限ループにいる
int side = (int)Math.Sqrt(TEST_FRAME); //検査枠の１辺の長さ
try
{
//cam0の画像を取得する処理
General.cam.FlagTestPic = true;
while (General.cam.FlagTestPic)
{
}
source = General.cam.imageForTest;
using (IplImage gray = Cv.CreateImage(new CvSize(WIDTH, HEIGHT), BitDepth.U8, 1)) // グレースケール画像格納用の変数
{
Cv.CvtColor(source, gray, ColorConversion.BgrToGray); // グレースケール変換
Cv.Threshold(gray, gray, State.camProp.BinLevel, 255, ThresholdType.Binary); // グレースケール画像を2値化
//ノイズ除去
if (State.camProp.Opening)
{
Cv.Erode(gray, gray, null, State.camProp.CloseCnt); //収縮処理
Cv.Dilate(gray, gray, null, State.camProp.OpenCnt); //膨張処理
}
{
Cv.Dilate(gray, gray, null, State.camProp.OpenCnt); //膨張処理
Cv.Erode(gray, gray, null, State.camProp.CloseCnt); //収縮処理
}
//デバッグ用コード（下記コメントを外すと画像を保存します）
//gray.SaveImage(@"C:\OS303\BinPic.bmp");
var mat = new OpenCvSharp.CPlusPlus.Mat(gray, true);
ListLedSpec.ForEach(l =>
{
int onCount = 0;
foreach (var i in Enumerable.Range(0, side))
{
foreach (var j in Enumerable.Range(0, side))
{
var re = mat.At <OpenCvSharp.CPlusPlus.Vec3b>((int)l.y - (side / 2) + i, (int)l.x - (side / 2) + j);
//点灯確認
if (re[0] == 255) //HSV=0,0,255 => 白
{
onCount++;
}
}
}
l.OnCount = onCount;
//ビューモデル更新
switch (l.name)
{
case NAME.LED1:
State.VmTestResults.LED1Value = l.OnCount.ToString("F0");
break;
case NAME.LED2:
State.VmTestResults.LED2Value = l.OnCount.ToString("F0");
break;
case NAME.LED3:
State.VmTestResults.LED3Value = l.OnCount.ToString("F0");
break;
}
});
}
}
catch
{
}
finally
{
General.cam.ResetFlag();//カメラのフラグを初期化 リトライ時にフラグが初期化できてないとだめ
}
}
public static bool CheckColor(NAME name)
{
State.SetCamProp();
General.cam.ResetFlag();//カメラのフラグを初期化 リトライ時にフラグが初期化できてないとだめ
//例 ＮＧリトライ時は、General.cam.FlagFrame = trueになっていてNGフレーム表示の無限ループにいる
int X = 0;
int Y = 0;
int HueMax = 0;
int HueMin = 0;
var ListH = new List <int>();
//var ListS = new List<int>();
//var ListV = new List<int>();
int side = (int)Math.Sqrt(TEST_FRAME);//検査枠の１辺の長さ
try
{
switch (name)
{
case NAME.LED1:
X = Int32.Parse(State.camProp.LED1.Split('/').ToArray()[0]);
Y = Int32.Parse(State.camProp.LED1.Split('/').ToArray()[1]);
HueMax = State.TestSpec.OrangeHueMax;
HueMin = State.TestSpec.OrangeHueMin;
break;
case NAME.LED2:
X = Int32.Parse(State.camProp.LED2.Split('/').ToArray()[0]);
Y = Int32.Parse(State.camProp.LED2.Split('/').ToArray()[1]);
HueMax = State.TestSpec.GreenHueMax;
HueMin = State.TestSpec.GreenHueMin;
break;
case NAME.LED3:
X = Int32.Parse(State.camProp.LED3.Split('/').ToArray()[0]);
Y = Int32.Parse(State.camProp.LED3.Split('/').ToArray()[1]);
HueMax = State.TestSpec.RedHueMax;
HueMin = State.TestSpec.RedHueMin;
break;
}
//cam0の画像を取得する処理
General.cam.FlagTestPic = true;
while (General.cam.FlagTestPic)
{
}
source = General.cam.imageForTest;
//デバッグ用コード（下記コメントを外すと画像を保存します）
//source.SaveImage(@"C:\OS303\ColorPic.bmp");
using (IplImage hsv = new IplImage(640, 360, BitDepth.U8, 3)) // グレースケール画像格納用の変数
{
//RGBからHSVに変換
Cv.CvtColor(source, hsv, ColorConversion.BgrToHsv);
OpenCvSharp.CPlusPlus.Mat mat = new OpenCvSharp.CPlusPlus.Mat(hsv, true);
foreach (var i in Enumerable.Range(0, side))
{
foreach (var j in Enumerable.Range(0, side))
{
var re = mat.At <OpenCvSharp.CPlusPlus.Vec3b>((int)Y - (side / 2) + i, (int)X - (side / 2) + j);
if (re[1] == 255 && re[2] == 255)
{
ListH.Add(re[0]);
}
}
}
switch (name)
{
case NAME.LED1: //黄色
H_Ave = ListH.Min();
break;
case NAME.LED2: //緑色
H_Ave = ListH.Max();
break;
case NAME.LED3: //赤色
H_Ave = ListH.Min();
break;
}
return(H_Ave >= HueMin && H_Ave <= HueMax);
}
}
finally
{
string hsvValue = H_Ave.ToString("F0");
ColorHSV hsv = new ColorHSV((float)Test_Led.H_Ave / 180, 1, 1);
var rgb = ColorConv.HSV2RGB(hsv);
var color = new SolidColorBrush(Color.FromRgb(rgb.R, rgb.G, rgb.B));
color.Freeze();//これ重要！！！
switch (name)
{
case NAME.LED1:
State.VmTestResults.HueLED1 = hsvValue;
State.VmTestResults.ColorLED1 = color;
break;
case NAME.LED2:
State.VmTestResults.HueLED2 = hsvValue;
State.VmTestResults.ColorLED2 = color;
break;
case NAME.LED3:
State.VmTestResults.HueLED3 = hsvValue;
State.VmTestResults.ColorLED3 = color;
break;
}
}
}
// Watershedアルゴリズムによる画像の領域分割
// パラメータ: 分割数(横), 分割数(縦), マーカサイズ
private OpenCvSharp.CPlusPlus.Mat procWatershed(OpenCvSharp.CPlusPlus.Mat matSrc, int wdiv, int hdiv, int msize)
{
// Matの準備
OpenCvSharp.CPlusPlus.Mat matDst = matSrc.Clone();
// IplImageの準備(C API用)
OpenCvSharp.IplImage iplSrc = matSrc.ToIplImage();
OpenCvSharp.IplImage iplDst = iplSrc.Clone();
// マーカ画像の準備
OpenCvSharp.IplImage iplMarker = new OpenCvSharp.IplImage(iplSrc.Size, OpenCvSharp.BitDepth.S32, 1);
iplMarker.Zero();
// マーカ設置(等分割)
OpenCvSharp.CvPoint[,] mpt = new OpenCvSharp.CvPoint[wdiv, hdiv];
for (int i = 0; i < wdiv; i++)
{
for (int j = 0; j < hdiv; j++)
{
mpt[i, j] = new OpenCvSharp.CvPoint((int)(iplSrc.Width / wdiv * (i + 0.5)), (int)(iplSrc.Height / hdiv * (j + 0.5)));
iplMarker.Circle(mpt[i, j], msize, OpenCvSharp.CvScalar.ScalarAll(i * wdiv + j), OpenCvSharp.Cv.FILLED, OpenCvSharp.LineType.Link8, 0);
}
}
// 分割実行
OpenCvSharp.Cv.Watershed(iplSrc, iplMarker);
// マーカの描画
for (int i = 0; i < wdiv; i++)
{
for (int j = 0; j < hdiv; j++)
{
iplDst.Circle(mpt[i, j], msize, OpenCvSharp.CvColor.White, 3, OpenCvSharp.LineType.Link8, 0);
}
}
// 領域境界の描画
for (int i = 0; i < iplMarker.Height; i++)
{
for (int j = 0; j < iplMarker.Width; j++)
{
int idx = (int)(iplMarker.Get2D(i, j).Val0);
if (idx == -1)
{
iplDst.Set2D(i, j, OpenCvSharp.CvColor.Red);
}
}
}
// IplImage -> Matに戻す
matDst = new OpenCvSharp.CPlusPlus.Mat(iplDst);
return matDst;
}
private void 読み込みToolStripMenuItem_Click(object sender, EventArgs e)
{
// データ読み込み
OpenFileDialog dialog = new OpenFileDialog();
if (dialog.ShowDialog() == DialogResult.OK)
{
this.matOrg = new OpenCvSharp.CPlusPlus.Mat(dialog.FileName);
this.matL = this.matOrg.Clone();
this.matR = this.matOrg.Clone();
this.outputImageL = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(matL);
this.outputImageR = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(matR);
this.outputZoom = 1.0;
this.outputShift = new Point(0, 0);
this.isMouseDrag = false;
this.mousePre = new Point(0, 0);
this.comboBoxProcL.SelectedIndex = 0;
this.comboBoxProcR.SelectedIndex = 0;
this.pictureBoxL.Invalidate();
this.pictureBoxR.Invalidate();
}
}
// 確率的Hough変換(Canny + Hough) + 統計情報
private OpenCvSharp.CPlusPlus.Mat procHoughStat(OpenCvSharp.CPlusPlus.Mat matSrc, int votes, double minLength, double maxGap)
{
OpenCvSharp.CPlusPlus.Mat matDst = matSrc.Clone();
OpenCvSharp.CPlusPlus.Mat matGray = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Mat matBinary = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Cv2.CvtColor(matSrc, matGray, OpenCvSharp.ColorConversion.BgraToGray, 1);
OpenCvSharp.CPlusPlus.Cv2.Threshold(matGray, matBinary, 0, 255, OpenCvSharp.ThresholdType.Binary | OpenCvSharp.ThresholdType.Otsu);
// Hough変換
double rho = 1.0; // 距離分解能
double theta = Math.PI / 180.0; // 角度分解能
OpenCvSharp.CvLineSegmentPoint[] lines = OpenCvSharp.CPlusPlus.Cv2.HoughLinesP(matBinary, rho, theta, votes, minLength, maxGap);
// 描画
Random rnd = new Random();
foreach (OpenCvSharp.CvLineSegmentPoint it in lines)
{
//matDst.Line(it.P1, it.P2, new OpenCvSharp.CPlusPlus.Scalar(0, 0, 255), 1, OpenCvSharp.LineType.AntiAlias, 0);
matDst.Line(it.P1, it.P2, new OpenCvSharp.CPlusPlus.Scalar(rnd.Next(0, 255), rnd.Next(0, 255), rnd.Next(0, 255)), 1, OpenCvSharp.LineType.AntiAlias, 0);
}
// 本数、平均長、最大長の計算と表示
//int divNumR = 10;
//int divNumC = 10;
int divSizeR = matDst.Rows / divNumR;
int divSizeC = matDst.Cols / divNumC;
//double[,] sum = new double[divNumR, divNumC];
//double[,] max = new double[divNumR, divNumC];
//int[,] num = new int[divNumR, divNumC];
foreach (OpenCvSharp.CvLineSegmentPoint it in lines)
{
double midR = (it.P1.Y + it.P2.Y) / 2;
double midC = (it.P1.X + it.P2.X) / 2;
double dist = it.P1.DistanceTo(it.P2);
for (int r = 0; r < divNumR; r++)
{
for (int c = 0; c < divNumC; c++)
{
if (midR >= divSizeR * r && midR < divSizeR * (r + 1) && midC >= divSizeC * c && midC < divSizeC * (c + 1))
{
sum[r, c] += dist;
num[r, c]++;
if (max[r, c] < dist)
{
max[r, c] = dist;
}
}
}
}
}
for (int r = 0; r < divNumR; r++)
{
matDst.Line(new OpenCvSharp.CPlusPlus.Point(0, divSizeR * r), new OpenCvSharp.CPlusPlus.Point(matDst.Cols, divSizeR * r), new OpenCvSharp.CPlusPlus.Scalar(0, 0, 255), 1, OpenCvSharp.LineType.AntiAlias, 0);
for (int c = 0; c < divNumC; c++)
{
matDst.Line(new OpenCvSharp.CPlusPlus.Point(divSizeC * c, 0), new OpenCvSharp.CPlusPlus.Point(divSizeC * c, matDst.Cols), new OpenCvSharp.CPlusPlus.Scalar(0, 0, 255), 1, OpenCvSharp.LineType.AntiAlias, 0);
if (num[r, c] > 0)
{
OpenCvSharp.CPlusPlus.Cv2.PutText(matDst, num[r, c].ToString(), new OpenCvSharp.CPlusPlus.Point(10 + divSizeC * c, 20 + divSizeR * r), OpenCvSharp.FontFace.HersheySimplex, 0.5, new OpenCvSharp.CPlusPlus.Scalar(0, 0, 255), 2, OpenCvSharp.LineType.AntiAlias);
OpenCvSharp.CPlusPlus.Cv2.PutText(matDst, (sum[r, c] / num[r, c]).ToString("F2"), new OpenCvSharp.CPlusPlus.Point(10 + divSizeC * c, 40 + divSizeR * r), OpenCvSharp.FontFace.HersheySimplex, 0.5, new OpenCvSharp.CPlusPlus.Scalar(0, 0, 255), 2, OpenCvSharp.LineType.AntiAlias);
OpenCvSharp.CPlusPlus.Cv2.PutText(matDst, max[r, c].ToString("F2"), new OpenCvSharp.CPlusPlus.Point(10 + divSizeC * c, 60 + divSizeR * r), OpenCvSharp.FontFace.HersheySimplex, 0.5, new OpenCvSharp.CPlusPlus.Scalar(0, 0, 255), 2, OpenCvSharp.LineType.AntiAlias);
}
}
}
return matDst;
}
// 画像ピラミッドを用いた画像の領域分割
// パラメータ: ピラミッドレベル, ピクセルを接続する閾値, クラスタリングの範囲の閾値
private OpenCvSharp.CPlusPlus.Mat procPyrSegmentation(OpenCvSharp.CPlusPlus.Mat matSrc, int level, double threshold1, double threshold2)
{
// Matの準備
OpenCvSharp.CPlusPlus.Mat matDst = matSrc.Clone();
// IplImageの準備(C API用)
OpenCvSharp.IplImage iplSrc = matSrc.ToIplImage();
OpenCvSharp.IplImage iplDst = iplSrc.Clone();
// ピラミッド画像作成のためのROI設定(2^levelで割り切れるサイズ)
OpenCvSharp.CvRect roi;
roi.X = 0;
roi.Y = 0;
roi.Width = iplSrc.Width & -(1 << level);
roi.Height = iplSrc.Height & -(1 << level);
iplSrc.SetROI(roi);
iplDst.SetROI(roi);
OpenCvSharp.Cv.PyrSegmentation(iplSrc, iplDst, level, threshold1, threshold2);
// IplImage -> Matに戻す
matDst = new OpenCvSharp.CPlusPlus.Mat(iplDst);
return matDst;
}
// 確率的Hough変換(Canny + Hough)
private OpenCvSharp.CPlusPlus.Mat procHough(OpenCvSharp.CPlusPlus.Mat matSrc, int votes, double minLength, double maxGap)
{
OpenCvSharp.CPlusPlus.Mat matDst = matSrc.Clone();
OpenCvSharp.CPlusPlus.Mat matCanny = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Cv2.Canny(matSrc, matCanny, 100, 200, 3);
// Hough変換
double rho = 1.0; // 距離分解能
double theta = Math.PI / 180.0; // 角度分解能
OpenCvSharp.CvLineSegmentPoint[] lines = OpenCvSharp.CPlusPlus.Cv2.HoughLinesP(matCanny, rho, theta, votes, minLength, maxGap);
// 描画
Random rnd = new Random();
foreach (OpenCvSharp.CvLineSegmentPoint it in lines)
{
//matDst.Line(it.P1, it.P2, new OpenCvSharp.CPlusPlus.Scalar(0, 0, 255), 1, OpenCvSharp.LineType.AntiAlias, 0);
matDst.Line(it.P1, it.P2, new OpenCvSharp.CPlusPlus.Scalar(rnd.Next(0, 255), rnd.Next(0, 255), rnd.Next(0, 255)), 1, OpenCvSharp.LineType.AntiAlias, 0);
}
return matDst;
}
// グレースケール化
private OpenCvSharp.CPlusPlus.Mat procGrayScale(OpenCvSharp.CPlusPlus.Mat matSrc)
{
OpenCvSharp.CPlusPlus.Mat matDst = matSrc.Clone();
OpenCvSharp.CPlusPlus.Mat matGray = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Cv2.CvtColor(matSrc, matGray, OpenCvSharp.ColorConversion.BgraToGray, 1);
OpenCvSharp.CPlusPlus.Cv2.CvtColor(matGray, matDst, OpenCvSharp.ColorConversion.GrayToBgra, 3);
return matDst;
}
// 輪郭抽出(グレースケール + 2値化 + 輪郭抽出)(輪郭のみの画像を戻す)
private OpenCvSharp.CPlusPlus.Mat procContour(OpenCvSharp.CPlusPlus.Mat matSrc)
{
OpenCvSharp.CPlusPlus.Mat matDst = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC3, new OpenCvSharp.CPlusPlus.Scalar(0, 0, 0));
OpenCvSharp.CPlusPlus.Mat matGray = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Mat matBinary = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Cv2.CvtColor(matSrc, matGray, OpenCvSharp.ColorConversion.BgraToGray, 1);
OpenCvSharp.CPlusPlus.Cv2.Threshold(matGray, matBinary, 0, 255, OpenCvSharp.ThresholdType.Binary | OpenCvSharp.ThresholdType.Otsu);
// 輪郭抽出
OpenCvSharp.CPlusPlus.Mat[] contours;
OpenCvSharp.CPlusPlus.Mat hierarchy = new OpenCvSharp.CPlusPlus.Mat();
OpenCvSharp.CPlusPlus.Cv2.FindContours(matBinary, out contours, hierarchy, OpenCvSharp.ContourRetrieval.Tree, OpenCvSharp.ContourChain.ApproxNone);
//OpenCvSharp.CPlusPlus.Cv2.FindContours(matBinary, out contours, hierarchy, OpenCvSharp.ContourRetrieval.Tree, OpenCvSharp.ContourChain.ApproxSimple);
//OpenCvSharp.CPlusPlus.Cv2.FindContours(matBinary, out contours, hierarchy, OpenCvSharp.ContourRetrieval.Tree, OpenCvSharp.ContourChain.ApproxTC89KCOS);
//OpenCvSharp.CPlusPlus.Cv2.FindContours(matBinary, out contours, hierarchy, OpenCvSharp.ContourRetrieval.Tree, OpenCvSharp.ContourChain.ApproxTC89L1);
// 描画
//OpenCvSharp.CPlusPlus.Cv2.DrawContours(matDst, contours, -1, new OpenCvSharp.CPlusPlus.Scalar(255, 255, 255), OpenCvSharp.Cv.FILLED, OpenCvSharp.LineType.AntiAlias, hierarchy);
OpenCvSharp.CPlusPlus.Cv2.DrawContours(matDst, contours, -1, new OpenCvSharp.CPlusPlus.Scalar(255, 255, 255), 1, OpenCvSharp.LineType.AntiAlias, hierarchy);
return matDst;
}
// エッジ抽出(Canny)
private OpenCvSharp.CPlusPlus.Mat procCanny(OpenCvSharp.CPlusPlus.Mat matSrc, double threshold1, double threshold2, int apertureSize)
{
OpenCvSharp.CPlusPlus.Mat matDst = matSrc.Clone();
OpenCvSharp.CPlusPlus.Mat matCanny = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Cv2.Canny(matSrc, matCanny, threshold1, threshold2, apertureSize);
OpenCvSharp.CPlusPlus.Cv2.CvtColor(matCanny, matDst, OpenCvSharp.ColorConversion.GrayToBgra, 3);
return matDst;
}
// 2値化(グレースケール化 + 2値化)
private OpenCvSharp.CPlusPlus.Mat procBinary(OpenCvSharp.CPlusPlus.Mat matSrc)
{
OpenCvSharp.CPlusPlus.Mat matDst = matSrc.Clone();
OpenCvSharp.CPlusPlus.Mat matGray = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Mat matBinary = new OpenCvSharp.CPlusPlus.Mat(matSrc.Rows, matSrc.Cols, OpenCvSharp.CPlusPlus.MatType.CV_8UC1);
OpenCvSharp.CPlusPlus.Cv2.CvtColor(matSrc, matGray, OpenCvSharp.ColorConversion.BgraToGray, 1);
OpenCvSharp.CPlusPlus.Cv2.Threshold(matGray, matBinary, 0, 255, OpenCvSharp.ThresholdType.Binary | OpenCvSharp.ThresholdType.Otsu);
OpenCvSharp.CPlusPlus.Cv2.CvtColor(matBinary, matDst, OpenCvSharp.ColorConversion.GrayToBgra, 3);
return matDst;
}
