/*
* public IplImage HoughLines_Point(IplImage src, int canny1, int canny2, int thresh, int sideData)
* {
* // cvHoughLines2
* // 확률적 허프 변환을 지정해 선분의 검출을 실시한다
*
* // (1) 화상 읽기
* IplImage srcImgStd = src.Clone();
* IplImage srcImgGray = new IplImage(src.Size, BitDepth.U8, 1);
*
* CvMemStorage storage = new CvMemStorage();
* CvSeq houghLines;
* Cv.CvtColor(srcImgStd, srcImgGray, ColorConversion.BgrToGray);
* Cv.Canny(srcImgGray, srcImgGray, canny1, canny2, ApertureSize.Size3);
* houghLines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Probabilistic, 1, Math.PI/180, thresh, 5, 0);
*
*
* LinePoints.Clear();
* int limit = Math.Min(houghLines.Total, 6);
* for (int i = 0; i < limit; i++)
* {
* CvLineSegmentPolar elem = houghLines.GetSeqElem<CvLineSegmentPolar>(i).Value;
* CvPoint pt1 = houghLines.GetSeqElem<CvLineSegmentPoint>(i).Value.P1;
* CvPoint pt2 = houghLines.GetSeqElem<CvLineSegmentPoint>(i).Value.P2;
*
* //Trace.WriteLine(pt1.X.ToString("000.00000 ") + pt1.Y.ToString("000.00000 ") + pt2.X.ToString("000.00000 ")+ pt2.Y.ToString("000.00000"));
*
* srcImgStd.Line(pt1, pt2, CvColor.Red, 1, LineType.AntiAlias, 0);
*
* LinePoints.Add(pt1);
* LinePoints.Add(pt2);
* }
* srcImgStd.Dispose();
* srcImgGray.Dispose();
* houghLines.Dispose();
* storage.Dispose();
* return srcImgStd;
* }
*/
public IplImage HoughLines_Point08(IplImage src, int canny1, int canny2, int thresh, int sideData)
{
List <CvPoint> LinePoints = new List <CvPoint>();
int lineMinLength = 0;
if (sideData == 0 && sideData == 2)
{
lineMinLength = src.Width / 2;
}
else
{
lineMinLength = src.Height / 2;
}
// cvHoughLines2
// 확률적 허프 변환을 지정해 선분의 검출을 실시한다
// (1) 화상 읽기
using (IplImage srcImgStd = src.Clone())
using (IplImage srcImgGray = new IplImage(src.Size, BitDepth.U8, 1))
{
Cv.CvtColor(srcImgStd, srcImgGray, ColorConversion.BgrToGray);
// (2) 허프변환을 위한 캐니엣지 처리
//Cv.Canny(srcImgGray, srcImgGray, 50, 200, ApertureSize.Size3);
Cv.Canny(srcImgGray, srcImgGray, canny1, canny2, ApertureSize.Size3);
houghLine = srcImgGray.Clone();
using (CvMemStorage storage = new CvMemStorage())
{
LinePoints.Clear();
// (3) 표준적 허프 변환에 의한 선의 검출과 검출된 선 그리기
CvSeq lines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Probabilistic, 1, Math.PI / 180, thresh, 5, 0);
int limit = Math.Min(lines.Total, 6);
for (int i = 0; i < limit; i++)
{
CvLineSegmentPolar elem = lines.GetSeqElem <CvLineSegmentPolar>(i).Value;
CvPoint pt1 = lines.GetSeqElem <CvLineSegmentPoint>(i).Value.P1;
CvPoint pt2 = lines.GetSeqElem <CvLineSegmentPoint>(i).Value.P2;
//Trace.WriteLine(pt1.X.ToString("000.00000 ") + pt1.Y.ToString("000.00000 ") + pt2.X.ToString("000.00000 ")+ pt2.Y.ToString("000.00000"));
srcImgStd.Line(pt1, pt2, CvColor.Red, 1, LineType.AntiAlias, 0);
LinePoints.Add(pt1);
LinePoints.Add(pt2);
houghLine = srcImgStd.Clone();
}
}
}
return(houghLine);
}
//=============================================================
//
// 古典的Hough変換処理
//
//=============================================================
private void HoughStd(PictureBox pbox, IplImage image)
{
IplImage gray;
IplImage canny;
IplImage hstd;
gray = Cv.CreateImage(image.Size, BitDepth.U8, 1);
canny = Cv.CreateImage(image.Size, BitDepth.U8, 1);
hstd = Cv.CreateImage(image.Size, BitDepth.U8, 3);
Cv.CvtColor(image, gray, ColorConversion.RgbToGray);
Cv.Canny(gray, canny, 50, 200);
Cv.CvtColor(canny, hstd, ColorConversion.GrayToRgb);
CvMemStorage storage = new CvMemStorage();
CvSeq lines = Cv.HoughLines2(canny, storage, HoughLinesMethod.Standard, 1, Math.PI / 180, 120);
for (int i = 0; i < lines.Total; i++)
{
CvLineSegmentPolar elem = lines.GetSeqElem <CvLineSegmentPolar>(i).Value;
float rho = elem.Rho;
float theta = elem.Theta;
double a = Math.Cos(theta);
double b = Math.Sin(theta);
double x0 = a * rho;
double y0 = b * rho;
CvPoint pt1 = new CvPoint(Cv.Round(x0 + 10000 * (-b)), Cv.Round(y0 + 10000 * (a)));
CvPoint pt2 = new CvPoint(Cv.Round(x0 - 10000 * (-b)), Cv.Round(y0 - 10000 * (a)));
Cv.Line(hstd, pt1, pt2, CvColor.Red, 1, LineType.AntiAlias, 0);
}
lines.Dispose();
storage.Dispose();
ViewBitmap(pbox, hstd);
Cv.ReleaseImage(gray);
Cv.ReleaseImage(canny);
Cv.ReleaseImage(hstd);
pictureBox2.Invalidate();
}
/// <summary>
/// sample of C style wrapper
/// </summary>
private void SampleC()
{
// cvHoughLines2
using (IplImage srcImgGray = new IplImage(FilePath.Image.Goryokaku, LoadMode.GrayScale))
using (IplImage srcImgStd = new IplImage(FilePath.Image.Goryokaku, LoadMode.Color))
using (IplImage srcImgProb = srcImgStd.Clone())
{
Cv.Canny(srcImgGray, srcImgGray, 50, 200, ApertureSize.Size3);
using (CvMemStorage storage = new CvMemStorage())
{
// Standard algorithm
CvSeq lines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Standard, 1, Math.PI / 180, 50, 0, 0);
// wrapper style
//CvLineSegmentPolar[] lines = src_img_gray.HoughLinesStandard(1, Math.PI / 180, 50, 0, 0);
int limit = Math.Min(lines.Total, 10);
for (int i = 0; i < limit; i++)
{
// native code style
/*
* unsafe
* {
* float* line = (float*)lines.GetElem<IntPtr>(i).Value.ToPointer();
* float rho = line[0];
* float theta = line[1];
* }
* //*/
// wrapper style
CvLineSegmentPolar elem = lines.GetSeqElem <CvLineSegmentPolar>(i).Value;
float rho = elem.Rho;
float theta = elem.Theta;
double a = Math.Cos(theta);
double b = Math.Sin(theta);
double x0 = a * rho;
double y0 = b * rho;
CvPoint pt1 = new CvPoint {
X = Cv.Round(x0 + 1000 * (-b)), Y = Cv.Round(y0 + 1000 * (a))
};
CvPoint pt2 = new CvPoint {
X = Cv.Round(x0 - 1000 * (-b)), Y = Cv.Round(y0 - 1000 * (a))
};
srcImgStd.Line(pt1, pt2, CvColor.Red, 3, LineType.AntiAlias, 0);
}
// Probabilistic algorithm
lines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Probabilistic, 1, Math.PI / 180, 50, 50, 10);
// wrapper style
//CvLineSegmentPoint[] lines = src_img_gray.HoughLinesProbabilistic(1, Math.PI / 180, 50, 0, 0);
for (int i = 0; i < lines.Total; i++)
{
// native code style
/*
* unsafe
* {
* CvPoint* point = (CvPoint*)lines.GetElem<IntPtr>(i).Value.ToPointer();
* src_img_prob.Line(point[0], point[1], CvColor.Red, 3, LineType.AntiAlias, 0);
* }
* //*/
// wrapper style
CvLineSegmentPoint elem = lines.GetSeqElem <CvLineSegmentPoint>(i).Value;
srcImgProb.Line(elem.P1, elem.P2, CvColor.Red, 3, LineType.AntiAlias, 0);
}
}
using (new CvWindow("Hough_line_standard", WindowMode.AutoSize, srcImgStd))
using (new CvWindow("Hough_line_probabilistic", WindowMode.AutoSize, srcImgProb))
{
CvWindow.WaitKey(0);
}
}
}
//HoughLines2()
//확률적 허프 변환을 지정해 선분의 검출을 실시한다
//1. CvArr* image : 변환을 할 이미지가 들어간다.
//2. void* line_storage : 라인을 저장할 공간
//3. int method : 허프변환에는 3개의 방법이 있다 . 이 방법을 설정하는 인자
//4. double rho / double theta : 이 둘은 얼마나 조밀한 단위(?)를 사용할 것인가를 정하는 인자 이다. (예로 rho=1이라면 1픽셀단위로 조사를 하고 theta = PI/180 이라면 1도 단위로 조사를 하겠다는 뜻)
//5. int threshold : 허프 공간상에 그려지는 곡선들이 중첩되는 부분을 이용해서 직선을 검출하는데 threshold 값보다 중첩되는 갯수가 많으면 직선으로 간주한다는 뜻이다. 숫자가 커지면 당연히 더 직선의 기준이 엄격하게 된다.
//6.double param1 : probabilistic 일 경우 직선의 최소 길이를 설정할 수 있다.
//7.double param2 : probabilistic 일 경우 직선의 최대 길이를 설정할 수 있다.
public IplImage HoughLines(IplImage src, IplImage boxImage, ref IplImage resultImage)
{
// cvHoughLines2
// 확률적 허프 변환을 지정해 선분의 검출을 실시한다
IplImage orImage = boxImage.Clone();
// (1) 화상 읽기
using (IplImage srcImgStd = src.Clone())
using (IplImage srcImgGray = new IplImage(src.Size, BitDepth.U8, 1))
{
Cv.CvtColor(srcImgStd, srcImgGray, ColorConversion.BgrToGray);
// (2) 허프변환을 위한 캐니엣지 처리
Cv.Canny(srcImgGray, srcImgGray, 50, 200, ApertureSize.Size3);
houghLine = srcImgGray.Clone();
int lineMinLength = srcImgStd.Width / 2;
int lineMaxLength = srcImgStd.Width;
using (CvMemStorage storage = new CvMemStorage())
{
// (3) 표준적 허프 변환에 의한 선의 검출과 검출된 선 그리기
CvSeq lines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Standard, 1, Math.PI / 180, 50, 0, 0);
int limit = Math.Min(lines.Total, 10);
for (int i = 0; i < limit; i++)
{
CvLineSegmentPolar elem = lines.GetSeqElem <CvLineSegmentPolar>(i).Value;
float rho = elem.Rho;
float theta = elem.Theta;
double a = Math.Cos(theta);
double b = Math.Sin(theta);
double x0 = a * rho;
double y0 = b * rho;
CvPoint pt1 = new CvPoint {
X = Cv.Round(x0 + src.Width * (-b)), Y = Cv.Round(y0 + src.Height * (a))
};
CvPoint pt2 = new CvPoint {
X = Cv.Round(x0 - src.Width * (-b)), Y = Cv.Round(y0 - src.Height * (a))
};
if (pt1.X < 1)
{
pt1.X = 0;
pt2.X = src.Width;
}
if (pt2.X < 1)
{
pt1.X = src.Width;
pt2.X = 0;
}
if (pt1.Y < 1)
{
pt1.Y = 0;
pt2.Y = src.Height;
}
if (pt2.Y < 1)
{
pt1.Y = src.Height;
pt2.Y = 0;
}
srcImgStd.Line(pt1, pt2, CvColor.Red, 1, LineType.AntiAlias, 0);
houghLine = srcImgStd.Clone();
orImage.Line(pt1, pt2, CvColor.Red, 1, LineType.AntiAlias, 0);
houghLine = orImage.Clone();
return(houghLine);
}
}
}
return(houghLine);
}
public IplImage HoughLines_Line(IplImage src, int canny1, int canny2, int thresh)
{
// cvHoughLines2
// 확률적 허프 변환을 지정해 선분의 검출을 실시한다
List <CvPoint> LinePoints = new List <CvPoint>();
// (1) 화상 읽기
using (IplImage srcImgStd = src.Clone())
using (IplImage srcImgGray = new IplImage(src.Size, BitDepth.U8, 1))
{
Cv.CvtColor(srcImgStd, srcImgGray, ColorConversion.BgrToGray);
// (2) 허프변환을 위한 캐니엣지 처리
//Cv.Canny(srcImgGray, srcImgGray, 50, 200, ApertureSize.Size3);
Cv.Canny(srcImgGray, srcImgGray, canny1, canny2, ApertureSize.Size3);
houghLine = srcImgGray.Clone();
using (CvMemStorage storage = new CvMemStorage())
{
LinePoints.Clear();
// (3) 표준적 허프 변환에 의한 선의 검출과 검출된 선 그리기
CvSeq lines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Standard, 1, Math.PI / 180, thresh, 0, 0);
//int limit = Math.Min(lines.Total, 10);
for (int i = 0; i < Math.Min(lines.Total, 3); i++)
{
CvLineSegmentPolar elem = lines.GetSeqElem <CvLineSegmentPolar>(i).Value;
float rho = elem.Rho;
float theta = elem.Theta;
double a = Math.Cos(theta), b = Math.Sin(theta);
double x0 = a * rho, y0 = b * rho;
CvPoint pt1, pt2;
//pt1.X = Cv.Round(x0 + 1000*(-b));
//pt1.Y = Cv.Round(y0 + 1000*(a));
//pt2.X = Cv.Round(x0 - 1000*(-b));
//pt2.Y = Cv.Round(y0 - 1000*(a));
pt1.X = Cv.Round(x0 + srcImgStd.Width * (-b));
pt1.Y = Cv.Round(y0 + srcImgStd.Height * (a));
pt2.X = Cv.Round(x0 - srcImgStd.Width * (-b));
pt2.Y = Cv.Round(y0 - srcImgStd.Height * (a));
if (pt1.X < 0)
{
pt1.X = 0;
pt2.X = src.Width;
}
else if (pt2.X < 0)
{
pt1.X = src.Width;
pt2.X = 0;
}
if (pt1.Y < 0)
{
pt1.Y = 0;
pt2.Y = src.Height;
}
else if (pt2.Y < 0)
{
pt1.Y = src.Height;
pt2.Y = 0;
}
//Trace.WriteLine(pt1.X.ToString("000.00000 ") + pt1.Y.ToString("000.00000 ") + pt2.X.ToString("000.00000 ") + pt2.Y.ToString("000.00000"));
srcImgStd.Line(pt1, pt2, CvColor.Red, 1, LineType.AntiAlias, 0);
LinePoints.Add(pt1);
LinePoints.Add(pt2);
houghLine = srcImgStd.Clone();
}
}
}
return(houghLine);
}
//private CvSeq houghLines;
//public IplImage srcImgGray = new IplImage();
//public IplImage srcImgStd = new IplImage();
//public CvMemStorage storage = new CvMemStorage();
public List <CvPoint> HoughLines_Point(IplImage src, int edge1, int edge2, int line1, int line2, int line3)
{
try
{
// 확률적 허프 변환을 지정해 선분의 검출을 실시한다
List <CvPoint> LinePoints = new List <CvPoint>();
IplImage srcImgStd = new IplImage(src.ROI.Size, BitDepth.U8, 3);
Cv.Copy(src, srcImgStd);
IplImage srcImgGray = new IplImage(src.ROI.Size, BitDepth.U8, 1);
Cv.CvtColor(srcImgStd, srcImgGray, ColorConversion.BgrToGray);
Cv.Canny(srcImgGray, srcImgGray, edge1, edge2, ApertureSize.Size3);
CvMemStorage storage = new CvMemStorage();
CvSeq houghLines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Probabilistic, 1, Math.PI / 180, line1, line2, line3);
//CvWindow.ShowImages(src);
//Hough_Lines_Point LinesFinder = new Hough_Lines_Point();
//LinesFinder.srcImgGray = new IplImage(src.Size, BitDepth.U8, 1);
//Cv.CvtColor(src, LinesFinder.srcImgGray, ColorConversion.BgrToGray);
//Cv.Canny(LinesFinder.srcImgGray, LinesFinder.srcImgGray, edge1, edge2, ApertureSize.Size3);
//CvMemStorage storage = new CvMemStorage();
//CvSeq houghLines = LinesFinder.srcImgGray.HoughLines2(storage, HoughLinesMethod.Probabilistic, 1, Math.PI / 180, line1, line2, line3);
//CvWindow.ShowImages(LinesFinder.srcImgGray);
//bool tmpFalg = true;
// for(int i = 1; i < 256;i++)
// {
// if (houghLines.Total >= 10)
// {
// break;
// }
// houghLines = LinesFinder.srcImgGray.HoughLines2(LinesFinder.storage, HoughLinesMethod.Probabilistic, 1, Math.PI / 180, 2, line2, line3);
// }
//LinePoints = new List<CvPoint>();
LinePoints.Clear();
int limit = Math.Min(houghLines.Total, 10);
for (int i = 0; i < limit; i++)
{
CvLineSegmentPolar elem = houghLines.GetSeqElem <CvLineSegmentPolar>(i).Value;
CvPoint pt1 = houghLines.GetSeqElem <CvLineSegmentPoint>(i).Value.P1;
CvPoint pt2 = houghLines.GetSeqElem <CvLineSegmentPoint>(i).Value.P2;
//Trace.WriteLine(pt1.X.ToString("000.00000 ") + pt1.Y.ToString("000.00000 ") + pt2.X.ToString("000.00000 ")+ pt2.Y.ToString("000.00000"));
//LinesFinder.srcImgStd.Line(LinesFinder.pt1, LinesFinder.pt2, CvColor.LawnGreen, 3, LineType.AntiAlias, 0);
//TestImage = LinesFinder.srcImgStd.Clone();
//src.Line(pt1, pt2, CvColor.LawnGreen, 3, LineType.AntiAlias, 0);
//CvWindow.ShowImages(src);
//TestImage = src.Clone();
LinePoints.Add(pt1);
LinePoints.Add(pt2);
}
srcImgStd.Dispose();
srcImgGray.Dispose();
houghLines.Dispose();
storage.Dispose();
return(LinePoints);
}
catch (Exception e)
{
MessageBox.Show(MethodBase.GetCurrentMethod().Name + " " + e.Message);
throw;
}
}
/// <summary>
/// sample of C style wrapper
/// </summary>
private void SampleC()
{
// cvHoughLines2
// 標準的ハフ変換と確率的ハフ変換を指定して線（線分）の検出を行なう．サンプルコード内の各パラメータ値は処理例の画像に対してチューニングされている．
// (1)画像の読み込み
using (IplImage srcImgGray = new IplImage(Const.ImageGoryokaku, LoadMode.GrayScale))
using (IplImage srcImgStd = new IplImage(Const.ImageGoryokaku, LoadMode.Color))
using (IplImage srcImgProb = srcImgStd.Clone())
{
// (2)ハフ変換のための前処理
Cv.Canny(srcImgGray, srcImgGray, 50, 200, ApertureSize.Size3);
using (CvMemStorage storage = new CvMemStorage())
{
// (3)標準的ハフ変換による線の検出と検出した線の描画
CvSeq lines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Standard, 1, Math.PI / 180, 50, 0, 0);
// wrapper style
//CvLineSegmentPolar[] lines = src_img_gray.HoughLinesStandard(1, Math.PI / 180, 50, 0, 0);
int limit = Math.Min(lines.Total, 10);
for (int i = 0; i < limit; i++)
{
// native code style
/*
* unsafe
* {
* float* line = (float*)lines.GetElem<IntPtr>(i).Value.ToPointer();
* float rho = line[0];
* float theta = line[1];
* }
* //*/
// wrapper style
CvLineSegmentPolar elem = lines.GetSeqElem <CvLineSegmentPolar>(i).Value;
float rho = elem.Rho;
float theta = elem.Theta;
double a = Math.Cos(theta);
double b = Math.Sin(theta);
double x0 = a * rho;
double y0 = b * rho;
CvPoint pt1 = new CvPoint {
X = Cv.Round(x0 + 1000 * (-b)), Y = Cv.Round(y0 + 1000 * (a))
};
CvPoint pt2 = new CvPoint {
X = Cv.Round(x0 - 1000 * (-b)), Y = Cv.Round(y0 - 1000 * (a))
};
srcImgStd.Line(pt1, pt2, CvColor.Red, 3, LineType.AntiAlias, 0);
}
// (4)確率的ハフ変換による線分の検出と検出した線分の描画
lines = srcImgGray.HoughLines2(storage, HoughLinesMethod.Probabilistic, 1, Math.PI / 180, 50, 50, 10);
// wrapper style
//CvLineSegmentPoint[] lines = src_img_gray.HoughLinesProbabilistic(1, Math.PI / 180, 50, 0, 0);
for (int i = 0; i < lines.Total; i++)
{
// native code style
/*
* unsafe
* {
* CvPoint* point = (CvPoint*)lines.GetElem<IntPtr>(i).Value.ToPointer();
* src_img_prob.Line(point[0], point[1], CvColor.Red, 3, LineType.AntiAlias, 0);
* }
* //*/
// wrapper style
CvLineSegmentPoint elem = lines.GetSeqElem <CvLineSegmentPoint>(i).Value;
srcImgProb.Line(elem.P1, elem.P2, CvColor.Red, 3, LineType.AntiAlias, 0);
}
}
// (5)検出結果表示用のウィンドウを確保し表示する
using (new CvWindow("Hough_line_standard", WindowMode.AutoSize, srcImgStd))
using (new CvWindow("Hough_line_probabilistic", WindowMode.AutoSize, srcImgProb))
{
CvWindow.WaitKey(0);
}
}
}
