// 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;
}
// 平均値シフト法による画像のセグメント化
// パラメータ: 空間窓の半径, 色空間窓の半径, セグメンテーションに用いるピラミッドの最大レベル
private OpenCvSharp.CPlusPlus.Mat procPyrMeanShiftFiltering(OpenCvSharp.CPlusPlus.Mat matSrc, double sp, double sr, int level)
{
// 終了パラメータ
OpenCvSharp.CPlusPlus.TermCriteria term = new OpenCvSharp.CPlusPlus.TermCriteria(OpenCvSharp.CriteriaType.Iteration, 5, 1);
//OpenCvSharp.CPlusPlus.TermCriteria term = new OpenCvSharp.CPlusPlus.TermCriteria(OpenCvSharp.CriteriaType.Epsilon, 5, 1);
// Matの準備
OpenCvSharp.CPlusPlus.Mat matDst = matSrc.Clone();
OpenCvSharp.CPlusPlus.Cv2.PyrMeanShiftFiltering(matSrc, matDst, sp, sr, level, term);
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) + 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;
}
// 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;
}
// 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;
}
