/**获取外包络矩形
* **/
public double[] GetBoundingBox(ModelParams para = ModelParams.bounding_box1)
{
HTuple boundingBox = GetParamValue(para);
double[] arry = boundingBox.ToDArr();//获取2个点，2个点可以转换成一个立方体
return(arry);
}
public double[] GetCoordZ(ModelParams para = ModelParams.point_coord_z)
{
HTuple Z = GetParamValue(para);
double[] arry = Z.ToDArr();
return(arry);
}
public double[] GetCoordY(ModelParams para = ModelParams.point_coord_y)
{
HTuple Y = GetParamValue(para);
double[] arry = Y.ToDArr();
return(arry);
}
/**获取点云的坐标
* **/
public double[] GetCoordX(ModelParams para = ModelParams.point_coord_x)
{
HTuple X = GetParamValue(para);
double[] arry = X.ToDArr();
return(arry);
}
public void ProcessStep(HImage imageGrabbed)
{
currentIVData.Image = imageGrabbed;
int imageChannels = imageGrabbed.CountChannels();
HImage rImg = null, gImg = null, bImg = null, rgbImg = null, irImg = null;
if (imageChannels == Properties.Settings.Default.NumberOfChannelsInIRAndRGBImage)
{
rImg = imageGrabbed.Decompose4(out gImg, out bImg, out irImg);
rgbImg = rImg.Compose3(gImg, bImg);
}
HImage grayImage = new HImage();
if (rgbImg == null)
{
return;
}
imageGrabbed = rgbImg.CopyImage();
lock (this.ImageToBeSaved)
{
this.ImageToBeSaved = imageGrabbed.CopyImage();
}
HImage ho_R;
HImage ho_G;
HImage ho_B;
ho_R = imageGrabbed.Decompose3(out ho_G, out ho_B);
HTuple RAOIGrayVals = Globals.GetGrayValuesOfLine(ho_R);
HTuple GAOIGrayVals = Globals.GetGrayValuesOfLine(ho_G);
HTuple BAOIGrayVals = Globals.GetGrayValuesOfLine(ho_B);
HTuple IRAOIGrayVals = Globals.GetGrayValuesOfLine(irImg);
currentIVData.GrayValues.RPlaneVals = RAOIGrayVals.ToDArr();
currentIVData.GrayValues.GPlaneVals = GAOIGrayVals.ToDArr();
currentIVData.GrayValues.BPlaneVals = BAOIGrayVals.ToDArr();
currentIVData.GrayValues.MPlaneVals = IRAOIGrayVals.ToDArr();
UpdateHistogramForImage();
}
public override void SaveConfig()
{
all_parm = OffsetXY + "_" + AngleRange + "_" + EnableRotateCenter + "_" + CalibDataFileName + "_";
all_parm += XMaxDeviation + "_" + YMaxDeviation + "_";
all_parm += CenterRow + "_" + CenterColumn + "_";
all_parm += DistanceMax + "_";
if (in_pixel_row != null)
{
int length = in_pixel_row.Length;
all_parm += length + "_";
for (int i = 0; i < length; i++)
{
all_parm += in_pixel_column.ToDArr()[i] + "_" + in_pixel_row.ToDArr()[i] + "_" + in_world_x.ToDArr()[i] + "_" + in_world_y.ToDArr()[i] + "_";
}
}
all_parm.Remove(all_parm.LastIndexOf("_"));
}
/// <summary>
/// 已测试
/// 软触发拍照下，计算相机的uv->xy坐标系变换的操作，如large相机
/// 要求之前设置好相机/光源/触发至“合理”状态
/// [x] = [ H1 H2 H3 ] [u]
/// [y] = [ H4 H5 H6 ] * [v]
/// [1]
/// </summary>
/// <param name="matUV2XY">uv->xy变换矩阵，将2*3的矩阵按照行堆叠的方式存储为1*6的数组, ref传递方式，需要数组有一个初始值</param>
/// <param name="cam">相机控制类，注意曝光时间需要设置合适。软触发拍照建议曝光时间在100ms左右</param>
/// <param name="modelID">匹配的ncc模板</param>
/// <param name="score_thresh">匹配分数，需要大于0.5</param>
/// <param name="axisPara">运动轴信息（xy插补），具体包括轴速，加速度</param>
/// <param name="initPoint">初始点，中间仅适用了xy信息，需要保证走到初始点时室内内包含完整的，可匹配的model</param>
/// <param name="lightInd">软触发拍照对应的光源id，需要事先设置好对应光源合适的时间</param>
/// <param name="axisInd">x，y轴号</param>
/// <param name="xyRange">计算变换时，以初始点为中心，随机走位的范围，单位mm</param>
/// <param name="nPoints">随机走位多少个点</param>
/// <param name="lightDelay">软触发拍照光源的延迟，单位us，典型值10us</param>
/// <param name="timeOut">单次运动的延迟，单位ms</param>
/// <param name="winID">(调试用）显示窗口ID</param>
/// <returns>操作是否成功</returns>
public bool calibUV2XY
(
int camInd,
ref HTuple matUV2XY,
Model model,
double xyRange,
int nPoints = 20
)
{
//if (model.ReadModel(CalibrUV2XYModelPath) == false)
//{
// HTUi.PopError("加载标定模版失败！");
// return false;
//}
string errMsg = "";
if (_station.operation.MultiAxisMove(_station.AxisXYZ, new double[] { _xUv2xy, _yUv2xy, _zUv2xy }, true, out errMsg) != 0)
{
HTUi.PopError("无法移动至标定点位置！");
return(false);
}
Thread.Sleep(200);
// App.obj_light.FlashMultiLight(LightUseFor.ScanPoint1st);
//if(_station.operation.SWPosTrig(_station.AxisX,out errMsg)!=0)
//{
// HTUi.PopError(errMsg);
// return false;
//}
Thread.Sleep(10);
if (image != null)
{
image.Dispose();
}
HOperatorSet.GenEmptyObj(out image);
if (_station.operation.CaputreOneImage(_station.CamereDev[camInd], "Halcon", out image, out errMsg) != 0)
{
HTUi.PopError("采集图像失败：" + errMsg);
return(false);
}
//3. match
HTuple u, v, angle;
bool status = matchModel(camInd, ref image, model, out u, out v, out angle);
HObject showRegion = new HObject();
showRegion.Dispose();
HOperatorSet.GenCrossContourXld(out showRegion, u, v, 512, 0);
_station._rtUi._fm.ShowImage(_station._rtUi._fm.htWindowCalibration, image, showRegion);
//image.Dispose();
if (!status)
{
HTUi.PopError("获取匹配初始位置图像失败");
return(false);
}
HTuple xArr = new HTuple(), yArr = new HTuple(), uArr = new HTuple(), vArr = new HTuple();
Random rand = new Random();
//4. for ... snap , match, add <u,v,x,y>
for (int i = 0; i < nPoints; i++)
{
DateTime t1 = DateTime.Now;
//大于或等于 0.0 且小于 1.0 的双精度浮点数
double x = (rand.NextDouble() - 0.5) * xyRange + _xUv2xy;
double y = (rand.NextDouble() - 0.5) * xyRange + _yUv2xy;
if (_station.operation.MultiAxisMove(new string[] { _station.AxisXYZ[0], _station.AxisXYZ[1], }, new double[] { x, y }, true, out errMsg) != 0)
{
HTUi.PopError("无法移动至标定点位置！");
return(false);
}
Thread.Sleep(200);;
//if (_station.operation.SWPosTrig(_station.AxisX, out errMsg) != 0)
//{
// HTUi.PopError(errMsg);
// return false;
//}
Thread.Sleep(10);
if (image != null)
{
image.Dispose();
}
HOperatorSet.GenEmptyObj(out image);
if (_station.operation.CaputreOneImage(_station.CamereDev[camInd], "Halcon", out image, out errMsg) != 0)
{
HTUi.PopError("采集图像失败：" + errMsg);
return(false);
}
if (matchModel(camInd, ref image, model, out u, out v, out angle)) //found something
{
xArr.Append(x); yArr.Append(y); uArr.Append(u); vArr.Append(v);
}
showRegion.Dispose();
HOperatorSet.GenCrossContourXld(out showRegion, u, v, 512, 0);
_station._rtUi._fm.ShowImage(_station._rtUi._fm.htWindowCalibration, image, showRegion);
//image.Dispose();
}
if (xArr.Length < 10)
{
HTUi.PopError("有效点数不够");
return(false);
}
//5. least square estimation
Matrix <double> In = Matrix <double> .Build.Dense(3, xArr.Length, 1.0); //by default In[2,:] = 1.0
Matrix <double> Out = Matrix <double> .Build.Dense(2, xArr.Length);
Out.SetRow(0, xArr.ToDArr());
Out.SetRow(1, yArr.ToDArr());
In.SetRow(0, uArr.ToDArr());
In.SetRow(1, vArr.ToDArr());
Matrix <double> A = vec2Mat(In, Out);
//6. move to center of uv space
double[] aArr = A.ToRowWiseArray(); //need to be tested
_station._calibrationUV2XYParameter = string.Join(",", aArr.ToArray());
//parse
if (matUV2XY == null)
{
matUV2XY = new HTuple();
}
for (int i = 0; i < 6; i++)
{
matUV2XY.Append(aArr[i]);
}
return(true);
}
public void ProcessStep(HImage imageGrabbed)
{
HTuple startTime = null;
HTuple endTime = null;
HOperatorSet.CountSeconds(out startTime);
HOperatorSet.CountSeconds(out endTime);
currentOnCameraFFCData = new OnCameraFFCData();
try
{
int imageChannels = imageGrabbed.CountChannels();
HImage rImg = null, gImg = null, bImg = null, rgbImg = null, irImg = null;
if (imageChannels == Properties.Settings.Default.NumberOfChannelsInIRAndRGBImage)
{
rImg = imageGrabbed.Decompose4(out gImg, out bImg, out irImg);
rgbImg = rImg.Compose3(gImg, bImg);
}
HImage grayImage = new HImage();
if (rgbImg == null)
{
return;
}
imageGrabbed = rgbImg.CopyImage();
lock (this.ImageToBeSaved)
{
this.ImageToBeSaved = imageGrabbed.CopyImage();
}
// Feed the image to the script
imageGrabbed = imageGrabbed.CropDomain();
currentOnCameraFFCData.Image = imageGrabbed;
if (this.CameraAcquisition.CurrentNumberOfChannels == Properties.Settings.Default.NumberOfChannelsInIRAndRGBImage)
{
HImage ho_R;
HImage ho_G;
HImage ho_B;
ho_R = imageGrabbed.Decompose3(out ho_G, out ho_B);
HTuple RAOIGrayValues = Globals.GetGrayValuesOfLine(ho_R);
HTuple GAOIGrayValues = Globals.GetGrayValuesOfLine(ho_G);
HTuple BAOIGrayValues = Globals.GetGrayValuesOfLine(ho_B);
HTuple IRAOIGrayValues = Globals.GetGrayValuesOfLine(irImg);
currentOnCameraFFCData.GrayValues.RPlaneVals = RAOIGrayValues.ToDArr();
currentOnCameraFFCData.GrayValues.GPlaneVals = GAOIGrayValues.ToDArr();
currentOnCameraFFCData.GrayValues.BPlaneVals = BAOIGrayValues.ToDArr();
currentOnCameraFFCData.GrayValues.MPlaneVals = IRAOIGrayValues.ToDArr();
}
else if (this.CameraAcquisition.CurrentNumberOfChannels == Properties.Settings.Default.NumberOfChannelsInMonoImage)
{
HTuple AOIGrayValues = Globals.GetGrayValuesOfLine(imageGrabbed);
currentOnCameraFFCData.GrayValues.MPlaneVals = AOIGrayValues.ToDArr();
}
HOperatorSet.CountSeconds(out endTime);
currentOnCameraFFCData.TimeTaken = (endTime - startTime).D * 1000;
}
catch (Exception ex)
{
string errorMessage = "Exception occurred during On-Camera FFC step. ";
errorMessage = errorMessage + " Error Message: " + ex.Message;
MessageBox.Show(errorMessage, "Camera Setup Tool", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
/// <summary>
/// Performs the PRNU.
/// </summary>
/// <remarks></remarks>
private void PerformPRNU()
{
try
{
this.btnFFC_FPN.Enabled = false;
this.btnFFC_PRNU.Enabled = false;
this.lblStatus.Text = "Performing PRNU...";
this.lblStatus.BackColor = Color.Yellow;
this.prnuDone = false;
Application.DoEvents();
string buffer;
string command;
bool bfcStatus = true;
HImage imageCropped;
currentOnCameraFFCData = new OnCameraFFCData();
HImage imageGrabbed = new HImage();
HImage ho_RGB = new HImage();
HImage ho_R = new HImage();
HImage ho_G = new HImage();
HImage ho_B = new HImage();
HImage ho_M = new HImage();
lock (this.ImageToBeSaved)
{
imageGrabbed = this.ImageToBeSaved.CopyImage();
}
ho_R = imageGrabbed.Decompose3(out ho_G, out ho_B);
ho_RGB = ho_R.Compose3(ho_G, ho_B);
int presentChannel = ho_RGB.CountChannels();
if (presentChannel == Properties.Settings.Default.NumberOfChannelsInColorImage)
{
lock (this.ImageToBeSaved)
{
ho_RGB = this.ImageToBeSaved.CopyImage();
}
ho_R = ho_RGB.Decompose3(out ho_G, out ho_B);
HTuple RAOIGrayVals = Globals.GetGrayValuesOfLine(ho_R);
HTuple GAOIGrayVals = Globals.GetGrayValuesOfLine(ho_G);
HTuple BAOIGrayVals = Globals.GetGrayValuesOfLine(ho_B);
currentOnCameraFFCData.Image = ho_RGB;
currentOnCameraFFCData.GrayValues.RPlaneVals = RAOIGrayVals.ToDArr();
currentOnCameraFFCData.GrayValues.GPlaneVals = GAOIGrayVals.ToDArr();
currentOnCameraFFCData.GrayValues.BPlaneVals = BAOIGrayVals.ToDArr();
bool lightIntensityOptimum = true;
imageCropped = ho_RGB.CropPart((this.CameraAcquisition.CurrentImageHeight / 2) - Properties.Settings.Default.FFCROIRectangleHeight,
(this.CameraAcquisition.CurrentImageWidth / 2) - Properties.Settings.Default.FFCROIRectangleWidth,
Properties.Settings.Default.FFCROIRectangleWidth * 2,
(this.CameraAcquisition.CurrentImageHeight / 2));
ho_R = imageCropped.Decompose3(out ho_G, out ho_B);
RAOIGrayVals = Globals.GetGrayValuesOfLine(ho_R);
GAOIGrayVals = Globals.GetGrayValuesOfLine(ho_G);
BAOIGrayVals = Globals.GetGrayValuesOfLine(ho_B);
if (Properties.Settings.Default.CheckForImproperCalibrationTarget)
{
int minGrayValue;
int maxGrayValue;
double[] tempLineProfileR = RAOIGrayVals.ToDArr();
double[] tempLineProfileG = GAOIGrayVals.ToDArr();
double[] tempLineProfileB = BAOIGrayVals.ToDArr();
lightIntensityOptimum &=
this.CameraAcquisition.IsLightIntensityLevelOptimum(tempLineProfileR, out minGrayValue, out maxGrayValue, Properties.Settings.Default.PRNUMinimumGrayLevelOffset) &&
this.CameraAcquisition.IsLightIntensityLevelOptimum(tempLineProfileG, out minGrayValue, out maxGrayValue, Properties.Settings.Default.PRNUMinimumGrayLevelOffset) &&
this.CameraAcquisition.IsLightIntensityLevelOptimum(tempLineProfileB, out minGrayValue, out maxGrayValue, Properties.Settings.Default.PRNUMinimumGrayLevelOffset);
}
if (!lightIntensityOptimum)
{
this.RefreshImageWindow(ho_RGB);
this.lblStatus.Text = Properties.Settings.Default.PRNULightIntensityNotOptimumMessage;
this.lblStatus.BackColor = Color.Red;
this.btnFFC_FPN.Enabled = true;
this.btnFFC_PRNU.Enabled = true;
Application.DoEvents();
return;
}
}
else if (presentChannel == Properties.Settings.Default.NumberOfChannelsInMonoImage)
{
lock (this.ImageToBeSaved)
{
ho_M = this.ImageToBeSaved.CopyImage();
}
HTuple MAOIGrayVals = Globals.GetGrayValuesOfLine(ho_M);
currentOnCameraFFCData.Image = ho_M;
currentOnCameraFFCData.GrayValues.MPlaneVals = MAOIGrayVals.ToDArr();
bool lightIntensityOptimum = true;
if (Properties.Settings.Default.CheckForImproperCalibrationTarget)
{
int minGrayValue;
int maxGrayValue;
double[] tempLineProfileM = MAOIGrayVals.ToDArr();
lightIntensityOptimum &=
this.CameraAcquisition.IsLightIntensityLevelOptimum(tempLineProfileM, out minGrayValue, out maxGrayValue, Properties.Settings.Default.PRNUMinimumGrayLevelOffset);
}
if (!lightIntensityOptimum)
{
this.RefreshImageWindow(ho_M);
this.lblStatus.Text = Properties.Settings.Default.PRNULightIntensityNotOptimumMessage;
this.lblStatus.BackColor = Color.Red;
this.btnFFC_FPN.Enabled = true;
this.btnFFC_PRNU.Enabled = true;
Application.DoEvents();
return;
}
}
command = Globals.e2vUC4CommandToDoOnCameraBFC + System.Environment.NewLine;
bfcStatus = Globals.ExecuteSerialCommand(
(uint)this.CameraAcquisition.CurrentCameraProperties.SerialPortIndex,
command,
out buffer,
5000,
1000);
command = Globals.e2vUC4CommandToSaveFFCToUserBank1 + System.Environment.NewLine;
bfcStatus &= Globals.ExecuteSerialCommand(
(uint)this.CameraAcquisition.CurrentCameraProperties.SerialPortIndex,
command,
out buffer,
1000,
2000);
command = Globals.e2vUC4CommandToSaveALLSettingsToUserBank1 + System.Environment.NewLine;
bfcStatus &= Globals.ExecuteSerialCommand((uint)this.CameraAcquisition.CurrentCameraProperties.SerialPortIndex,
command,
out buffer,
1000,
2000);
if (bfcStatus)
{
lblStatus.Text = "On Camera Bright Field Correction Done";
lblStatus.BackColor = Color.LimeGreen;
}
else
{
lblStatus.Text = "On Camera Bright Field Correction not done properly";
lblStatus.BackColor = Color.Red;
}
this.prnuDone = bfcStatus;
this.btnFFC_FPN.Enabled = true;
this.btnFFC_PRNU.Enabled = true;
if (this.fpnDone && this.prnuDone)
{
this.CameraAcquisition.CurrentCameraSetupProperties.LastOnCameraFFCSavingDate = "";
this.CameraAcquisition.CurrentCameraSetupProperties.LastOnCameraFFCSavingDate = DateTime.Now.Day.ToString() + "-" +
DateTime.Now.Month.ToString() + "-" + DateTime.Now.Year.ToString() + " " +
DateTime.Now.Hour.ToString() + ":" + DateTime.Now.Minute.ToString() + ":" +
DateTime.Now.Second.ToString();
}
}
catch (System.Exception ex)
{
lblStatus.Text = "On Camera Bright Field Correction not done properly";
lblStatus.BackColor = Color.Red;
this.btnFFC_FPN.Enabled = true;
this.btnFFC_PRNU.Enabled = true;
this.prnuDone = false;
MessageBox.Show("Exception occurred while performing PRNU.\r\n Error: " + ex.Message,
"Camera Setup Tool", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
/// <summary>
/// Performs the FPN.
/// </summary>
/// <remarks></remarks>
private void PerformFPN()
{
this.btnFFC_FPN.Enabled = false;
this.btnFFC_PRNU.Enabled = false;
this.lblStatus.Text = "Performing FPN...";
this.lblStatus.BackColor = Color.Yellow;
this.fpnDone = false;
Application.DoEvents();
string buffer;
string command;
bool dfcStatus = true;
currentOnCameraFFCData = new OnCameraFFCData();
HImage imageGrabbed = new HImage();
HImage ho_RGB = new HImage();
HImage ho_R = new HImage();
HImage ho_G = new HImage();
HImage ho_B = new HImage();
HImage ho_M = new HImage();
try
{
lock (this.ImageToBeSaved)
{
imageGrabbed = this.ImageToBeSaved.CopyImage();
}
ho_R = imageGrabbed.Decompose3(out ho_G, out ho_B);
ho_RGB = ho_R.Compose3(ho_G, ho_B);
int presentChannel = ho_RGB.CountChannels();
if (presentChannel == Properties.Settings.Default.NumberOfChannelsInColorImage)
{
//ho_R = ho_RGB.Decompose3(out ho_G, out ho_B);
HTuple RAOIGrayVals = Globals.GetGrayValuesOfLine(ho_R);
HTuple GAOIGrayVals = Globals.GetGrayValuesOfLine(ho_G);
HTuple BAOIGrayVals = Globals.GetGrayValuesOfLine(ho_B);
currentOnCameraFFCData.Image = ho_RGB;
currentOnCameraFFCData.GrayValues.RPlaneVals = RAOIGrayVals.ToDArr();
currentOnCameraFFCData.GrayValues.GPlaneVals = GAOIGrayVals.ToDArr();
currentOnCameraFFCData.GrayValues.BPlaneVals = BAOIGrayVals.ToDArr();
HTuple maxGrayValueInCenterLineR = RAOIGrayVals.TupleMax();
HTuple maxGrayValueInCenterLineG = GAOIGrayVals.TupleMax();
HTuple maxGrayValueInCenterLineB = BAOIGrayVals.TupleMax();
if ((maxGrayValueInCenterLineR.I > Properties.Settings.Default.DarkFieldCorrectionMaximumGrayLevel) ||
(maxGrayValueInCenterLineG.I > Properties.Settings.Default.DarkFieldCorrectionMaximumGrayLevel) ||
(maxGrayValueInCenterLineB.I > Properties.Settings.Default.DarkFieldCorrectionMaximumGrayLevel))
{
this.RefreshImageWindow(ho_RGB);
this.lblStatus.Text = Properties.Settings.Default.FPNLightIntensityNotOptimumMessage;
this.lblStatus.BackColor = Color.Red;
this.btnFFC_FPN.Enabled = true;
this.btnFFC_PRNU.Enabled = true;
//Application.DoEvents();
return;
}
}
else if (this.CameraAcquisition.CurrentNumberOfChannels == Properties.Settings.Default.NumberOfChannelsInMonoImage)
{
lock (this.ImageToBeSaved)
{
ho_M = this.ImageToBeSaved.CopyImage();
}
HTuple MAOIGrayVals = Globals.GetGrayValuesOfLine(ho_M);
currentOnCameraFFCData.Image = ho_M;
currentOnCameraFFCData.GrayValues.MPlaneVals = MAOIGrayVals.ToDArr();
HTuple maxGrayValueInCenterLineM = MAOIGrayVals.TupleMax();
if (maxGrayValueInCenterLineM.I > Properties.Settings.Default.DarkFieldCorrectionMaximumGrayLevel)
{
this.RefreshImageWindow(ho_M);
this.lblStatus.Text = Properties.Settings.Default.FPNLightIntensityNotOptimumMessage;
this.lblStatus.BackColor = Color.Red;
this.btnFFC_FPN.Enabled = true;
this.btnFFC_PRNU.Enabled = true;
//Application.DoEvents();
return;
}
}
command = Globals.e2vUC4CommandToDoOnCameraDFC + System.Environment.NewLine;
dfcStatus = Globals.ExecuteSerialCommand((uint)this.CameraAcquisition.CurrentCameraProperties.SerialPortIndex,
command,
out buffer,
2000,
1000);
command = Globals.e2vUC4CommandToSaveFFCToUserBank1 + System.Environment.NewLine;
dfcStatus &= Globals.ExecuteSerialCommand((uint)this.CameraAcquisition.CurrentCameraProperties.SerialPortIndex,
command,
out buffer,
1000,
2000);
command = Globals.e2vUC4CommandToSaveALLSettingsToUserBank1 + System.Environment.NewLine;
dfcStatus &= Globals.ExecuteSerialCommand((uint)this.CameraAcquisition.CurrentCameraProperties.SerialPortIndex,
command,
out buffer,
1000,
2000);
if (dfcStatus)
{
lblStatus.Text = "On Camera Dark Field Correction Done";
lblStatus.BackColor = Color.LimeGreen;
}
else
{
lblStatus.Text = "On Camera Dark Field Correction not done properly";
lblStatus.BackColor = Color.Red;
}
this.fpnDone = dfcStatus;
this.btnFFC_FPN.Enabled = true;
this.btnFFC_PRNU.Enabled = true;
}
catch (System.Exception ex)
{
lblStatus.Text = "On Camera Dark Field Correction not done properly";
lblStatus.BackColor = Color.Red;
this.btnFFC_FPN.Enabled = true;
this.btnFFC_PRNU.Enabled = true;
this.fpnDone = false;
MessageBox.Show("Exception occurred while performing FPN.\r\n Error: " + ex.Message,
"Camera Setup Tool", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
public void ProcessStep(HImage imageGrabbed)
{
HTuple startTime = null;
HTuple endTime = null;
HOperatorSet.CountSeconds(out startTime);
HOperatorSet.CountSeconds(out endTime);
currentLSAData = new LightStickAlignmentData();
HImage imageCropped = new HImage();
try
{
int imageChannels = imageGrabbed.CountChannels();
HImage rImg = null, gImg = null, bImg = null, rgbImg = null, irImg = null;
if (imageChannels == Properties.Settings.Default.NumberOfChannelsInIRAndRGBImage)
{
rImg = imageGrabbed.Decompose4(out gImg, out bImg, out irImg);
rgbImg = rImg.Compose3(gImg, bImg);
}
HImage grayImage = new HImage();
if (rgbImg == null)
{
return;
}
imageGrabbed = rgbImg.CopyImage();
int presentImageNoOfChannels = imageGrabbed.CountChannels();
lock (this.ImageToBeSaved)
{
this.ImageToBeSaved = imageGrabbed.CopyImage();
}
// Feed the image to the script
imageGrabbed = imageGrabbed.CropDomain();
currentLSAData.Image = imageGrabbed;
if (imageChannels == Properties.Settings.Default.NumberOfChannelsInIRAndRGBImage)
{
HImage ho_R;
HImage ho_G;
HImage ho_B;
ho_R = imageGrabbed.Decompose3(out ho_G, out ho_B);
HTuple RAOIGrayValues = Globals.GetGrayValuesOfLine(ho_R);
HTuple GAOIGrayValues = Globals.GetGrayValuesOfLine(ho_G);
HTuple BAOIGrayValues = Globals.GetGrayValuesOfLine(ho_B);
HTuple IRAOIGrayVals = Globals.GetGrayValuesOfLine(irImg);
currentLSAData.GrayValues.RPlaneVals = RAOIGrayValues.ToDArr();
currentLSAData.GrayValues.GPlaneVals = GAOIGrayValues.ToDArr();
currentLSAData.GrayValues.BPlaneVals = BAOIGrayValues.ToDArr();
currentLSAData.GrayValues.MPlaneVals = IRAOIGrayVals.ToDArr();
imageCropped = imageGrabbed.CropPart((this.CameraAcquisition.CurrentImageHeight / 2) - Properties.Settings.Default.LICROIRectangleHeight,
(this.CameraAcquisition.CurrentImageWidth / 2) - Properties.Settings.Default.LICROIRectangleWidth,
Properties.Settings.Default.LICROIRectangleWidth * 2,
(this.CameraAcquisition.CurrentImageHeight / 2));
ho_R = imageCropped.Decompose3(out ho_G, out ho_B);
RAOIGrayValues = Globals.GetGrayValuesOfLine(ho_R);
// Clipping the pixels at Left & Right of the line
RAOIGrayValues = RAOIGrayValues.TupleSelectRange(
this.cameraAcquisition.CurrentCameraProperties.NumberOfPixelsToBeClippedAtLeft,
(Properties.Settings.Default.LICROIRectangleWidth * 2) - this.cameraAcquisition.CurrentCameraProperties.NumberOfPixelsToBeClippedAtRight);
// Update the labels showing the results of light uniformity check
int RminGrayValue;
int RmaxGrayValue;
// Checking whether the gray values is within the defined range in RED plane
bool RPlaneOptimum = this.cameraAcquisition.IsLightIntensityLevelOptimum(RAOIGrayValues.ToDArr(), out RminGrayValue, out RmaxGrayValue);
currentLSAData.MinGrayValue = RminGrayValue;
currentLSAData.MaxGrayValue = RmaxGrayValue;
currentLSAData.Status = RPlaneOptimum;
}
else if (this.cameraAcquisition.CurrentNumberOfChannels == Properties.Settings.Default.NumberOfChannelsInMonoImage)
{
HTuple AOIGrayValues = Globals.GetGrayValuesOfLine(imageGrabbed);
currentLSAData.GrayValues.MPlaneVals = AOIGrayValues.ToDArr();
// Clipping the pixels at Left & Right of the line
AOIGrayValues = AOIGrayValues.TupleSelectRange(
this.cameraAcquisition.CurrentCameraProperties.NumberOfPixelsToBeClippedAtLeft,
this.cameraAcquisition.CurrentImageWidth - this.cameraAcquisition.CurrentCameraProperties.NumberOfPixelsToBeClippedAtRight);
// Update the labels showing the results of light uniformity check
int minGrayValue;
int maxGrayValue;
// Checking whether the gray values is within the defined range in MONO plane
bool MonoPlaneOptimum = this.cameraAcquisition.IsLightIntensityLevelOptimum(AOIGrayValues.ToDArr(), out minGrayValue, out maxGrayValue);
currentLSAData.MinGrayValue = minGrayValue;
currentLSAData.MaxGrayValue = maxGrayValue;
currentLSAData.Status = MonoPlaneOptimum;
}
HOperatorSet.CountSeconds(out endTime);
currentLSAData.TimeTaken = (endTime - startTime).D * 1000;
this.BeginInvoke(new Action(UpdateStepUI));
}
catch (Exception ex)
{
string errorMessage = "Exception occurred during light intensity check. ";
errorMessage = errorMessage + " Error Message: " + ex.Message;
//MessageBox.Show(errorMessage, "Camera Setup Tool", MessageBoxButtons.OK, MessageBoxIcon.Error);
this.BeginInvoke(new Action(UpdateStepUI));
//lblStatus.Text = errorMessage;
//lblStatus.BackColor = Color.Red;
}
}
public void ProcessStep(HImage imageGrabbed)
{
currentFMCData = new FocusMagnificationCheckData();
lock (this.ImageToBeSaved)
{
this.ImageToBeSaved = imageGrabbed.CopyImage();
}
bool calibrationTargetContrastOK = true;
// Feed the image to the script
imageGrabbed = imageGrabbed.CropDomain();
currentFMCData.Image = imageGrabbed;
int imageChannels = imageGrabbed.CountChannels();
HImage rImg = null, gImg = null, bImg = null, rgbImg = null, irImg = null;
if (imageChannels == Properties.Settings.Default.NumberOfChannelsInIRAndRGBImage)
{
rImg = imageGrabbed.Decompose4(out gImg, out bImg, out irImg);
rgbImg = rImg.Compose3(gImg, bImg);
}
HImage grayImage = new HImage();
if (rgbImg == null)
{
return;
}
imageGrabbed = rgbImg.CopyImage();
#region IntensityCheckForCheckingCalibrationTarget
// Check the minimum and maximum light intensity to determine whether correct calibration target
// has been placed
grayImage = imageGrabbed.Rgb1ToGray();
HImage ho_R;
HImage ho_G;
HImage ho_B;
ho_R = imageGrabbed.Decompose3(out ho_G, out ho_B);
HTuple RAOIGrayVals = Globals.GetGrayValuesOfLine(ho_R);
HTuple GAOIGrayVals = Globals.GetGrayValuesOfLine(ho_G);
HTuple BAOIGrayVals = Globals.GetGrayValuesOfLine(ho_B);
HTuple IRAOIGrayVals = Globals.GetGrayValuesOfLine(irImg);
currentFMCData.GrayValues.RPlaneVals = RAOIGrayVals.ToDArr();
currentFMCData.GrayValues.GPlaneVals = GAOIGrayVals.ToDArr();
currentFMCData.GrayValues.BPlaneVals = BAOIGrayVals.ToDArr();
currentFMCData.GrayValues.MPlaneVals = IRAOIGrayVals.ToDArr();
int RPlaneMinValue;
int RPlaneMaxValue;
RAOIGrayVals = RAOIGrayVals.TupleSelectRange(this.CameraAcquisition.CurrentCameraProperties.NumberOfPixelsToBeClippedAtLeft,
this.CameraAcquisition.CurrentImageWidth - this.CameraAcquisition.CurrentCameraProperties.NumberOfPixelsToBeClippedAtRight);
calibrationTargetContrastOK = this.CameraAcquisition.IsLightIntensityLevelOptimum(GAOIGrayVals.ToDArr(), out RPlaneMinValue, out RPlaneMaxValue);
calibrationTargetContrastOK = (RPlaneMaxValue - RPlaneMinValue) > Properties.Settings.Default.FocusPatternCheckReferenceGrayValue;
#endregion
#region FindPatternArea
//Finds the pattern area
HImage reducedImage = Globals.FindPatternArea(grayImage);
if (reducedImage == null)
{
SetFocusStatusMessage("Image is too dark or Incorrect Pattern", Color.Red);
currentFMCData.FocusPercentage = "";
currentFMCData.MagnificationPercentage = "";
currentFMCData.PixelResolution = "";
//this.BeginInvoke(new Action<FocusMagnificationCheckData>(UpdateFocusMagnificationStepUI), currentFMCData);
return;
}
#endregion
#region Focus Learning
hv_focus = new HTuple();
HTuple hv_currentSharpness = new HTuple();
HImage imageCropped = new HImage();
//Indicates that execution has entered the focus learning stage
//(For both successful and failed learning)
bool focusLearningDone = false;
if (this.focusLearningStarted)
{
#region FocusLearningStage
focusLearningDone = true;
if (!this.focusLearningOver)
{
HTuple hv_Scale;
HTuple hv_Subsampling = 1;
hv_Scale = 1.0 / hv_Subsampling;
int grabbedImageWidth, grabbedImageHeight;
imageGrabbed.GetImageSize(out grabbedImageWidth, out grabbedImageHeight);
// Crop the image before learning
imageCropped = imageGrabbed.CropPart((this.CameraAcquisition.CurrentImageHeight / 2) - Properties.Settings.Default.FocusROIRectangleHeight,
(this.CameraAcquisition.CurrentImageWidth / 2) - Properties.Settings.Default.FocusROIRectangleWidth,
Properties.Settings.Default.FocusROIRectangleWidth * 2,
(this.CameraAcquisition.CurrentImageHeight / 2));
int croppedImageWidth, croppedImageHeight;
imageCropped.GetImageSize(out croppedImageWidth, out croppedImageHeight);
int noOfSamples = croppedImageHeight / Properties.Settings.Default.NoOfSamplesUsedInFocusStep;
for (int i = 0; i < Properties.Settings.Default.NoOfSamplesUsedInFocusStep; i++)
{
try
{
int row = i * noOfSamples;
HImage newCroppedImage = imageCropped.CopyImage().CropPart(row, 0, croppedImageWidth, noOfSamples);
//newCroppedImage.WriteImage("bmp", 0, "D:\\imageCropped" + i.ToString());
// Function Call for sharpness Measurement
hv_currentSharpness = MeasureSharpness(newCroppedImage, hv_Scale);
hv_AutoCorrelationTuple = hv_AutoCorrelationTuple.TupleConcat(hv_currentSharpness);
}
catch (Exception ex)
{
}
}
currentFMCData.FocusPercentage = "";
SetFocusStatusMessage("Learning...", Color.Yellow);
UpdateLabelMessage(currentFMCData.FocusPercentage);
}
else
{
hv_MaxAutoCorrelation = new HTuple();
HTuple hv_Change = new HTuple();
if (hv_AutoCorrelationTuple.TupleLength() > 0)
{
hv_MaxAutoCorrelation = hv_AutoCorrelationTuple.TupleMax();
hv_Change = ((hv_AutoCorrelationTuple.TupleMax() - hv_AutoCorrelationTuple.TupleMin()) / hv_AutoCorrelationTuple.TupleMax()) * 100;
if (hv_MaxAutoCorrelation.D <= 0.0 || hv_Change.D < Properties.Settings.Default.MinimumFocusLearningRangeRequired)
{
currentFMCData.FocusPercentage = "";
SetFocusStatusMessage("Focus Learning not done properly. Range of focus learning is not enough.", Color.Orange);
this.focusLearningOver = false;
UpdateLabelMessage(currentFMCData.FocusPercentage);
}
else
{
this.CameraAcquisition.CurrentCameraSetupProperties.FocusMaxAutoCorrelationValue = hv_MaxAutoCorrelation.D;
}
}
else
{
currentFMCData.FocusPercentage = "";
SetFocusStatusMessage("Focus Learning not done properly. Sharpness measurement failed", Color.Orange);
this.focusLearningOver = false;
UpdateLabelMessage(currentFMCData.FocusPercentage);
}
this.focusLearningStarted = false;
}
#endregion
}
else if (this.focusLearningOver)
{
#region FocusTestingPhase
if (!calibrationTargetContrastOK)
{
currentFMCData.FocusPercentage = "";
currentFMCData.MagnificationPercentage = "";
currentFMCData.PixelResolution = "";
SetFocusStatusMessage("Incorrect Pattern. Not enough contrast", Color.Red);
UpdateLabelMessage(currentFMCData.FocusPercentage);
return;
}
HTuple hv_Scale;
HTuple hv_Subsampling = 1;
hv_Scale = 1.0 / hv_Subsampling;
// Crop the image before learning
imageCropped = imageGrabbed.CropPart((this.CameraAcquisition.CurrentImageHeight / 2) - Properties.Settings.Default.FocusROIRectangleHeight,
(this.CameraAcquisition.CurrentImageWidth / 2) - Properties.Settings.Default.FocusROIRectangleWidth,
Properties.Settings.Default.FocusROIRectangleWidth * 2,
(this.CameraAcquisition.CurrentImageHeight / 2));
// Function Call for sharpness Measurement
hv_currentSharpness = MeasureSharpness(imageCropped, hv_Scale);
if (hv_currentSharpness > hv_MaxAutoCorrelation + 2)
{
SetFocusStatusMessage("Current sharpness is more than learnt sharpness. Insert valid calibration doc or Re-do focus learning !!", Color.Orange);
currentFMCData.PixelResolution = "";
currentFMCData.MagnificationPercentage = "";
currentFMCData.FocusPercentage = "";
UpdateLabelMessage(currentFMCData.FocusPercentage);
return;
}
else if (hv_currentSharpness > hv_MaxAutoCorrelation)
{
hv_MaxAutoCorrelation = hv_currentSharpness;
hv_AutoCorrelationTuple = hv_AutoCorrelationTuple.TupleConcat(hv_currentSharpness);
}
hv_focus = 100 - (((hv_MaxAutoCorrelation - hv_currentSharpness) / hv_MaxAutoCorrelation) * 100);
hv_focus = hv_focus.TupleRound();
currentFMCData.FocusPercentage = hv_focus.ToString();
if (hv_focus > 100)
{
// Not Focused
currentFMCData.FocusPercentage = "";
SetFocusStatusMessage("Focus learning not done properly", Color.Red);
UpdateLabelMessage(currentFMCData.FocusPercentage);
}
if (hv_focus >= 95 && hv_focus <= 100)
{
// Focused
SetFocusStatusMessage("Focused", Color.LimeGreen);
}
else if (hv_focus > 70 && hv_focus < 95)
{
//// Fine Tuning is required
SetFocusStatusMessage("Fine Tuning is required", Color.Yellow);
}
else
{
// Not Focused
SetFocusStatusMessage("Not focused", Color.Red);
}
#endregion
}
else if (!focusLearningOver && !focusLearningDone)
{
if (hv_MaxAutoCorrelation == null)
{
SetFocusStatusMessage("Focus learning not done", Color.Yellow);
}
}
UpdateLabelMessage(currentFMCData.FocusPercentage);
#endregion
}
public ResultFinShell DealFinShell(ParFinShell par, Hashtable htResult)
{
#region 定义
HTuple num_Obj = 0;
ResultFinShell result = new ResultFinShell();
HTuple width = null;
HTuple height = null;
ImageAll imageAll = null;
HObject ho_Image = null;
HObject ho_RegionReduced = null;
HObject ho_ResultPreprocess = null;
HObject ho_RegionOuter = null;
HObject ho_RegionInnerOuter = null;
HObject ho_RegionInner = null;
HObject ho_RegionIntersected = null;
HObject ho_RegionConnected = null;
HObject ho_RegionFillUp = null;
HObject ho_RegionOpening = null;
HObject ho_RegionClosing = null;
HObject ho_RegionWidthSelected = null;
HObject ho_RegionHeightSelected = null;
HObject ho_RegionAreaSelected = null;
HObject ho_RegionUnion1 = null;
HObject ho_RegionUnion2 = null;
HObject ho_RegionFinShell = null;
//求取沿XLD外形切线方向的外轮廓
HObject ho_xldToCalHeight = null;
HObject ho_xldToCalWidth = null;
HObject ho_ho_RegionFinShellSelect = null;
HObject ho_ho_RegionFinShellSelectContours = null;
HTuple hv_disMin = null;
double HeightCalUpper = 0;
HTuple WidthCalRow = null, WidthCalCol = null;
HTuple hv_FinShellIntersectRow = null;
HTuple hv_FinShellIntersectCol = null;
HTuple hv_FinShellCircleRadius = null;
HTuple FinShellWidth = null;
HOperatorSet.GenEmptyObj(out ho_Image);
HOperatorSet.GenEmptyObj(out ho_RegionReduced);
HOperatorSet.GenEmptyObj(out ho_ResultPreprocess);
HOperatorSet.GenEmptyObj(out ho_RegionOuter);
HOperatorSet.GenEmptyObj(out ho_RegionInnerOuter);
HOperatorSet.GenEmptyObj(out ho_RegionInner);
HOperatorSet.GenEmptyObj(out ho_RegionIntersected);
HOperatorSet.GenEmptyObj(out ho_RegionConnected);
HOperatorSet.GenEmptyObj(out ho_RegionFillUp);
HOperatorSet.GenEmptyObj(out ho_RegionOpening);
HOperatorSet.GenEmptyObj(out ho_RegionClosing);
HOperatorSet.GenEmptyObj(out ho_RegionWidthSelected);
HOperatorSet.GenEmptyObj(out ho_RegionHeightSelected);
HOperatorSet.GenEmptyObj(out ho_RegionAreaSelected);
HOperatorSet.GenEmptyObj(out ho_RegionUnion1);
HOperatorSet.GenEmptyObj(out ho_RegionUnion2);
HOperatorSet.GenEmptyObj(out ho_RegionFinShell);
HOperatorSet.GenEmptyObj(out ho_xldToCalHeight);
HOperatorSet.GenEmptyObj(out ho_xldToCalWidth);
HOperatorSet.GenEmptyObj(out ho_ho_RegionFinShellSelect);
HOperatorSet.GenEmptyObj(out ho_ho_RegionFinShellSelectContours);
HTuple hv_Area = null;
HTuple hv_CenterRow = null;
HTuple hv_CenterCol = null;
HTuple hv_Row = null;
HTuple hv_Column = null;
HTuple hv_Row2 = null;
HTuple hv_Column2 = null;
HTuple hv_Phi = null;
HTuple hv_Width = null;
HTuple hv_Height = null;
#endregion 定义
try
{
#region 基础功能调用
//if (BasicImageProcess(par, result, htResult, out ho_RegionReduced, out ho_Image, out width, out height))
//{
//}
//else
//{
// return result;
//}
#endregion 基础功能调用
//获取图像预处理结果，图像是二值化后再进行处理
ho_ResultPreprocess = result.g_ResultPreProcess.ImageResult.Ho_Image;
#region 真实轮廓
//string nameStdEdge = par.NameCellActualEdge;
string nameStdEdge = "C9";
/***** 得到当前片的平滑轮廓******/
ResultRaisedEdge resultRaise = (ResultRaisedEdge)htResult[nameStdEdge];
if (resultRaise == null)
{
result.LevelError_e = LevelError_enum.OK;
result.Annotation = par.NameCell.ToString() + ",当前片的平滑轮廓获取异常";
result.SetDefault();
return(result);
}
HObject ho_StdEdge = ((ImageAll)resultRaise.HtResultImage["C9FunRaisedEdge.RegionRemainingRemovedSmoothed"]).Ho_Image;
#endregion 真实轮廓
//以下为崩缺检查的算法
//获取图像预处理结果，图像是二值化后再进行处理
ho_ResultPreprocess = result.g_ResultPreProcess.ImageResult.Ho_Image;
//通过残留检查平滑后的轮廓获取平行的ROI区域
ho_RegionOuter.Dispose();
ho_RegionInner.Dispose();
ho_RegionInnerOuter.Dispose();
GenParalRegionFromXld(ho_StdEdge, out ho_RegionOuter, out ho_RegionInnerOuter, out ho_RegionInner, par.Width_Paral, par.OuterStdShift_Paral, par.InnerStdShift_Paral);
HObject ho_PreRegion = result.g_ResultPreProcess.resultBinary.RegionResult.Ho_Image;
ho_RegionIntersected.Dispose();
if (par.WorkingRegion == "Outer")//残留检测，选区为边缘外侧
{
HOperatorSet.Intersection(ho_PreRegion, ho_RegionOuter, out ho_RegionIntersected);
}
else if (par.WorkingRegion == "Inner")//崩缺检测，选区为边缘内侧
{
HOperatorSet.Intersection(ho_ResultPreprocess, ho_RegionInner, out ho_RegionIntersected);
}
else
{
return(result);
}
HOperatorSet.CountObj(ho_RegionIntersected, out num_Obj);
if (num_Obj == 0)
{
result.LevelError_e = LevelError_enum.OK;
result.Annotation = par.NameCell.ToString() + ",选区内无异常";
result.SetDefault();
return(result);
}
ho_RegionConnected.Dispose();
HOperatorSet.Connection(ho_RegionIntersected, out ho_RegionConnected);
ho_RegionFillUp.Dispose();
HOperatorSet.FillUp(ho_RegionConnected, out ho_RegionFillUp);
#region 开运算，闭运算
ho_RegionOpening.Dispose();
if (par.OpeningCircle != 0)
{
HOperatorSet.OpeningCircle(ho_RegionFillUp, out ho_RegionOpening, par.OpeningCircle);
}
else
{
ho_RegionOpening = ho_RegionFillUp.Clone();
}
HOperatorSet.CountObj(ho_RegionOpening, out num_Obj);
if (num_Obj == 0)
{
result.LevelError_e = LevelError_enum.OK;
result.Annotation = par.NameCell.ToString() + ",开运算后异常点消失";
result.SetDefault();
return(result);
}
ho_RegionClosing.Dispose();
if (par.ClosingCircle != 0)
{
HOperatorSet.ClosingCircle(ho_RegionOpening, out ho_RegionClosing, par.ClosingCircle);
}
else
{
ho_RegionClosing = ho_RegionOpening.Clone();
}
#endregion 开运算，闭运算
//把贝壳宽度/高度/面积超出阈值的，都挑选出来
ho_RegionWidthSelected.Dispose();
ho_RegionHeightSelected.Dispose();
ho_RegionAreaSelected.Dispose();
HOperatorSet.SelectShape(ho_RegionClosing, out ho_RegionWidthSelected, "width", "and", par.MinWidth, par.MaxWidth);
HOperatorSet.SelectShape(ho_RegionWidthSelected, out ho_RegionHeightSelected, "height", "and", par.MinHeight, par.MaxHeight);
HOperatorSet.SelectShape(ho_RegionHeightSelected, out ho_RegionAreaSelected, "area", "and", par.MinArea, par.MaxArea);
ho_RegionUnion1.Dispose();
//HOperatorSet.Union2(ho_RegionWidthSelected, ho_RegionHeightSelected, out ho_RegionUnion1);
ho_RegionUnion2.Dispose();
//HOperatorSet.Union2(ho_RegionUnion1, ho_RegionAreaSelected, out ho_RegionUnion2);
HOperatorSet.CountObj(ho_RegionAreaSelected, out num_Obj);
if (num_Obj == 0)
{
result.LevelError_e = LevelError_enum.OK;
result.Annotation = par.NameCell.ToString() + ",区域特征提取后异常点消失";
result.SetDefault();
return(result);
}
//提取到的贝壳(Shell)OR残留(Fin)
ho_RegionFinShell.Dispose();
ho_RegionFinShell = ho_RegionAreaSelected.Clone();
//HOperatorSet.Connection(ho_RegionUnion2, out ho_RegionFinShell);
//对获取到的残留或者崩缺进行blob分析
HOperatorSet.AreaCenter(ho_RegionFinShell, out hv_Area, out hv_CenterRow, out hv_CenterCol);
double[] dblHeightArry = new double[hv_CenterRow.Length];//存放高度值的数组
double[] dblWidthArry = new double[hv_CenterRow.Length];
#region 求取包络
switch (par.SmallestSurround_e)
{
case SmallestSurround_enum.Rect2:
HOperatorSet.SmallestRectangle2(ho_RegionFinShell, out hv_Row, out hv_Column, out hv_Phi, out hv_Width, out hv_Height);
break;
case SmallestSurround_enum.Circle:
HOperatorSet.SmallestCircle(ho_RegionFinShell, out hv_Row, out hv_Column, out hv_Width);
break;
case SmallestSurround_enum.TanLineRect:
if (par.WorkingRegion == "Outer") //残留检测，选区为边缘外侧
{
HeightCalUpper = par.OuterStdShift_Paral + par.Width_Paral * 1.5;
HOperatorSet.GenParallelContourXld(ho_StdEdge, out ho_xldToCalHeight, "regression_normal", HeightCalUpper);
HOperatorSet.GenParallelContourXld(ho_StdEdge, out ho_xldToCalWidth, "regression_normal", par.OuterStdShift_Paral);
}
else //崩缺检测，选区为边缘内测
{
HeightCalUpper = par.InnerStdShift_Paral + par.Width_Paral * 1.5;
HOperatorSet.GenParallelContourXld(ho_StdEdge, out ho_xldToCalHeight, "regression_normal", -HeightCalUpper);
HOperatorSet.GenParallelContourXld(ho_StdEdge, out ho_xldToCalWidth, "regression_normal", -par.InnerStdShift_Paral);
}
for (int j = 0; j < hv_CenterRow.Length; j++)
{
try
{
HOperatorSet.SelectObj(ho_RegionFinShell, out ho_ho_RegionFinShellSelect, j + 1);
HOperatorSet.GenContourRegionXld(ho_ho_RegionFinShellSelect, out ho_ho_RegionFinShellSelectContours, "border");
//求残留区域和参考xld平行的XLD
//HObject ho_ContoursIntersected = null;
//HObject ho_TestImage = null;
//HObject ho_TestImageResult = null;
//HOperatorSet.GenImageConst(out ho_TestImage, "byte", width, height);
//HOperatorSet.PaintXld(ho_xldToCalHeight, ho_TestImage, out ho_TestImageResult, 255);
//HOperatorSet.PaintXld(ho_ho_RegionFinShellSelectContours, ho_TestImageResult, out ho_TestImageResult, 255);
//HOperatorSet.WriteImage(ho_TestImageResult, "bmp", 128, "E:\\DOC\\德龙\\0427测试\\XKY4.27\\TestImage"+j.ToString());
//计算残留高度
HOperatorSet.DistanceCcMin(ho_xldToCalHeight, ho_ho_RegionFinShellSelectContours, "fast_point_to_segment", out hv_disMin);
dblHeightArry[j] = Math.Round(HeightCalUpper - hv_disMin.D, 1);
HOperatorSet.IntersectionContoursXld(ho_xldToCalWidth, ho_ho_RegionFinShellSelectContours, "mutual", out hv_FinShellIntersectRow, out hv_FinShellIntersectCol, out hv_FinShellCircleRadius);
double dblFinShellWidth = 0;
HTuple hv_WidthTemp;
double[] IntersectPointRow = hv_FinShellIntersectRow.DArr;
double[] IntersectPointCol = hv_FinShellIntersectCol.DArr;
//求取边缘上最远的两个点的距离
for (int k = 0; k < hv_FinShellIntersectRow.Length - 1; k++)
{
for (int l = k + 1; l < hv_FinShellIntersectRow.Length; l++)
{
HOperatorSet.DistancePp(IntersectPointRow[k], IntersectPointCol[k], IntersectPointRow[l], IntersectPointCol[l], out hv_WidthTemp);
if (hv_WidthTemp.D > dblFinShellWidth)
{
dblFinShellWidth = hv_WidthTemp.D;
}
}
}
//HOperatorSet.GenContourPolygonXld(out ho_ContoursIntersected, hv_FinShellIntersectRow, hv_FinShellIntersectCol);
//HOperatorSet.LengthXld(ho_ContoursIntersected, out FinShellWidth);
//计算残留宽度
dblWidthArry[j] = Math.Round(dblFinShellWidth, 1);
}
catch
{
}
}
break;
default: //默认矩形1
HOperatorSet.SmallestRectangle1(ho_RegionFinShell, out hv_Row, out hv_Column, out hv_Row2, out hv_Column2);
break;
}
#endregion 求取包络
double x = 0;
double y = 0;
for (int j = 0; j < hv_CenterRow.Length; j++)
{
#region 输出坐标类型
switch (par.TypeOutCoord)
{
case "面积中心":
x = Math.Round(hv_CenterCol.ToDArr()[j], 0);
y = Math.Round(hv_CenterRow.ToDArr()[j], 0);
break;
case "包络中心":
if (par.SmallestSurround_e == SmallestSurround_enum.Rect1)
{
x = Math.Round((hv_Column.ToDArr()[j] + hv_Column2.ToDArr()[j]) / 2, 3);
y = Math.Round((hv_Row.ToDArr()[j] + hv_Row2.ToDArr()[j]) / 2, 3);
}
else
{
x = Math.Round(hv_Column.ToDArr()[j], 3);
y = Math.Round(hv_Row.ToDArr()[j], 3);
}
break;
}
#endregion 输出坐标类型
result.X_L.Add(x);
result.Y_L.Add(y);
result.Area_L.Add(hv_Area.IArr[j]);//求取面积
result.Rectangularity_L.Add(0);
result.Circularity_L.Add(0);
#region 求取包络的集合
switch (par.SmallestSurround_e)
{
case SmallestSurround_enum.Rect2:
result.R_L.Add(Math.Round(hv_Phi.DArr[j], 5)); //求取角度
result.Height_L.Add(Math.Round(hv_Height.DArr[j], 3)); //获取矩形的长宽
result.Width_L.Add(Math.Round(hv_Width.DArr[j], 3));
result.Radius_L.Add(0);
break;
case SmallestSurround_enum.Circle:
result.Radius_L.Add(Math.Round(hv_Width.DArr[j], 3));
result.R_L.Add(0);
result.Height_L.Add(0);
result.Width_L.Add(0);
break;
case SmallestSurround_enum.TanLineRect: //切线矩形，即为方向与xld切线平行方向的矩形
result.Radius_L.Add(0);
result.R_L.Add(0);
result.Height_L.Add(dblHeightArry[j]);
result.Width_L.Add(dblWidthArry[j]);
break;
default: //默认矩形1
result.R_L.Add(0);
double rectWidth = (hv_Column2.IArr[j] - hv_Column.IArr[j]) / 2;
result.Width_L.Add(Math.Round(rectWidth, 3));
double rectHeight = (hv_Row2.IArr[j] - hv_Row.IArr[j]) / 2;
result.Height_L.Add(Math.Round(rectHeight, 3));
result.Radius_L.Add(0);
break;
}
#endregion 求取包络的集合
}
//区域个数
result.Num = result.X_L.Count;
if (result.Num == 0)
{
result.LevelError_e = LevelError_enum.OK;
result.Annotation = par.NameCell.ToString() + "FinShell个数为0";
result.SetDefault();
}
//添加显示
AddDisplay(par.g_ParOutput, result);
return(result);
}
catch (Exception ex)
{
return(result);
}
finally
{
//对结果进行综合处理
SetComprehensiveResult(result, par, htResult, false);
//校准
DealCalibResult(par, result, htResult);
#region 记录时间
WriteRunTime(stopWatch, NameClass, par, result);
#endregion 记录时间
#region 记录
RecordHoject(par, result, NameClass, "RegionReduced", ho_RegionReduced);
RecordHoject(par, result, NameClass, "RegionInner", ho_RegionInner);
RecordHoject(par, result, NameClass, "RegionOuter", ho_RegionOuter);
RecordHoject(par, result, NameClass, "RegionInnerOuter", ho_RegionInnerOuter);
RecordHoject(par, result, NameClass, "RegionIntersected", ho_RegionIntersected);
RecordHoject(par, result, NameClass, "RegionConnected", ho_RegionConnected);
RecordHoject(par, result, NameClass, "RegionFillUp", ho_RegionFillUp);
RecordHoject(par, result, NameClass, "RegionOpening", ho_RegionOpening);
RecordHoject(par, result, NameClass, "RegionClosing", ho_RegionClosing);
RecordHoject(par, result, NameClass, "RegionWidthSelected", ho_RegionWidthSelected);
RecordHoject(par, result, NameClass, "RegionHeightSelected", ho_RegionHeightSelected);
RecordHoject(par, result, NameClass, "RegionAreaSelected", ho_RegionAreaSelected);
RecordHoject(par, result, NameClass, "RegionUnion1", ho_RegionUnion1);
RecordHoject(par, result, NameClass, "RegionUnion2", ho_RegionUnion2);
RecordHoject(par, result, NameClass, "RegionFinShell", ho_RegionFinShell);
#endregion 记录
ho_xldToCalHeight.Dispose();
ho_xldToCalWidth.Dispose();
ho_ho_RegionFinShellSelect.Dispose();
ho_ho_RegionFinShellSelectContours.Dispose();
}
}
public void DealSmoothing(ParRaisedEdgeSmooth parRaisedEdgeSmooth, HObject ho_ImageBinary, HObject ho_RegionBinary, ResultRaisedEdge result, Hashtable htResult)
{
ParSmooth par = parRaisedEdgeSmooth.g_ParSmooth;
#region 定义
HObject ho_ROI = null;
HObject ho_FilterROI = null;
HObject ho_FilterInverseROI = null;
// Local control variables
HTuple hv_Width = null, hv_Height = null;
HTuple hv_RowInit = new HTuple(), hv_ColInit = new HTuple();
HTuple hv_Row1 = null, hv_Col1 = null;
HTuple hv_Row2 = null, hv_Col2 = null;
HTuple hv_AreaDilation = new HTuple(), hv_RowDilation = new HTuple();
HTuple hv_ColumnDilation = new HTuple(), hv_NumberSmooth = new HTuple();
HTuple hv_RowS = new HTuple();
HTuple hv_ColS = new HTuple(), hv_InvertedCol = new HTuple();
HTuple hv_InvertedRow = new HTuple(), hv_ConcatCol = new HTuple();
HTuple hv_ConcatRow = new HTuple(), hv_NumberRegionDilation1 = new HTuple();
// Local iconic variables
//怎么把图片和region导入
HObject ho_ImageReduced;
HObject ho_Region, ho_RegionDilation;
HObject ho_rectErosion1, ho_BorderOrigin;
HObject ho_ConnectedRegionDilation = null;
HObject ho_BinImage = null;
HObject ho_ImageBinReduced = null, ho_BorderOriginal = null, ho_SmoothedBoaderOriginal = null;
HObject ho_SelectedSmoothedContours = null, ho_ObjectSelected = null;
HObject ho_ContourConcat = null, ho_RegionParall = null, ho_ImageParall = null;
HObject ho_RegionError = null, ho_ConnectedRegions = null, ho_RegionErosionError = null;
HObject ho_RegionDilationError = null;
//求取缺陷
HObject ho_BorderFull = null;
HObject ho_SmoothedContoursFull = null;
HObject ho_ParaFull = null;
HObject ho_ParaRegionFull = null;
HObject ho_RegionROIFull = null;
HObject ho_ErrorFull = null;
HObject ho_FilterErrorFull = null;//崩缺求取中，剪掉台阶面崩缺后的缺陷
HObject ho_ErrorRegioinFull = null;
HObject ho_ErrorConnectFull = null;
HObject ho_ErrorSelectFull = null;
HObject ho_ErrorXldFull = null;
HObject ho_SmoothedContoursFullLongest = null;
HOperatorSet.GenEmptyObj(out ho_SmoothedContoursFullLongest);
HOperatorSet.GenEmptyObj(out ho_ImageReduced);
HOperatorSet.GenEmptyObj(out ho_Region);
HOperatorSet.GenEmptyObj(out ho_RegionDilation);
HOperatorSet.GenEmptyObj(out ho_rectErosion1);
HOperatorSet.GenEmptyObj(out ho_BorderOrigin);
HOperatorSet.GenEmptyObj(out ho_ConnectedRegionDilation);
HOperatorSet.GenEmptyObj(out ho_BinImage);
HOperatorSet.GenEmptyObj(out ho_ImageBinReduced);
HOperatorSet.GenEmptyObj(out ho_BorderOriginal);
HOperatorSet.GenEmptyObj(out ho_SmoothedBoaderOriginal);
HOperatorSet.GenEmptyObj(out ho_SelectedSmoothedContours);
HOperatorSet.GenEmptyObj(out ho_ObjectSelected);
HOperatorSet.GenEmptyObj(out ho_ContourConcat);
HOperatorSet.GenEmptyObj(out ho_RegionParall);
HOperatorSet.GenEmptyObj(out ho_ImageParall);
HOperatorSet.GenEmptyObj(out ho_RegionError);
HOperatorSet.GenEmptyObj(out ho_ConnectedRegions);
HOperatorSet.GenEmptyObj(out ho_RegionErosionError);
HOperatorSet.GenEmptyObj(out ho_RegionDilationError);
HOperatorSet.GenEmptyObj(out ho_BorderFull);
HOperatorSet.GenEmptyObj(out ho_SmoothedContoursFull);
HOperatorSet.GenEmptyObj(out ho_FilterInverseROI);
HOperatorSet.GenEmptyObj(out ho_FilterErrorFull);
HOperatorSet.GenEmptyObj(out ho_ParaFull);
HOperatorSet.GenEmptyObj(out ho_ParaRegionFull);
#endregion 定义
try
{
int smooth = (par.SmoothValue / 2) * 2 + 1;//平滑系数只能是奇数
HOperatorSet.GetImageSize(ho_ImageBinary, out hv_Width, out hv_Height);
//求取ROI
FunROI funCirROI = new FunROI();
bool blResult = false;
string anno = "";
ho_ROI = funCirROI.CreateOneROI(parRaisedEdgeSmooth.g_ParROI.g_ParROIExcute_L[0], htResult, out blResult, out anno);
//对ROI区域进行腐蚀，剔除多余轮廓的边界
HOperatorSet.ErosionCircle(ho_ROI, out ho_rectErosion1, 20);
HOperatorSet.ReduceDomain(ho_ImageBinary, ho_rectErosion1, out ho_ImageReduced);
//通过ROI截图
HOperatorSet.Intersection(ho_RegionBinary, ho_ROI, out ho_RegionDilation);
//对二值化图片求取轮廓
HOperatorSet.ThresholdSubPix(ho_ImageReduced, out ho_BorderOrigin, 100);
//迭代十次
for (int i = 0; i < par.Num; i++)
{
hv_Row1 = new HTuple();
hv_Col1 = new HTuple();
hv_Row2 = new HTuple();
hv_Col2 = new HTuple();
//剔除主体之外的噪声点
ho_ConnectedRegionDilation.Dispose();
HOperatorSet.Connection(ho_RegionDilation, out ho_ConnectedRegionDilation);
HOperatorSet.AreaCenter(ho_ConnectedRegionDilation, out hv_AreaDilation, out hv_RowDilation, out hv_ColumnDilation);
ho_RegionDilation.Dispose();
//保留主体
HOperatorSet.SelectShape(ho_ConnectedRegionDilation, out ho_RegionDilation, "area", "and", 50000, int.MaxValue);
//主题二值化以后的图片
ho_BinImage.Dispose();
HOperatorSet.RegionToBin(ho_RegionDilation, out ho_BinImage, 255, 0, hv_Width, hv_Height);
//二值化缩减轮廓
ho_ImageBinReduced.Dispose();
HOperatorSet.ReduceDomain(ho_BinImage, ho_rectErosion1, out ho_ImageBinReduced);
//***************************
//生成带有方向梯度的边界，用平滑后的边界和原始边界的平移生成轮廓处理
//生成内边界
ho_BorderOriginal.Dispose();
HOperatorSet.ThresholdSubPix(ho_ImageBinReduced, out ho_BorderOriginal, 100);
//角点非圆弧
ho_SmoothedBoaderOriginal.Dispose();
HOperatorSet.SmoothContoursXld(ho_BorderOriginal, out ho_SmoothedBoaderOriginal, smooth);
//筛选轮廓
ho_SelectedSmoothedContours.Dispose();
HOperatorSet.SelectContoursXld(ho_SmoothedBoaderOriginal, out ho_SelectedSmoothedContours, "contour_length", par.SelectAreaLow, 99999999, -0.5, 0.5);
HOperatorSet.CountObj(ho_SelectedSmoothedContours, out hv_NumberSmooth);
if ((int)(new HTuple(hv_NumberSmooth.TupleGreater(1))) != 0)
{
int numSmooth = hv_NumberSmooth.ToIArr()[0] - 1;
for (int j = 0; j < numSmooth; j++)
{
ho_ObjectSelected.Dispose();
HOperatorSet.SelectObj(ho_SelectedSmoothedContours, out ho_ObjectSelected, j + 1);
HOperatorSet.GetContourXld(ho_ObjectSelected, out hv_RowS, out hv_ColS);
HOperatorSet.TupleConcat(hv_RowInit, hv_RowS, out hv_RowInit);
HOperatorSet.TupleConcat(hv_ColInit, hv_ColS, out hv_ColInit);
}
}
else
{
HOperatorSet.GetContourXld(ho_SelectedSmoothedContours, out hv_RowInit, out hv_ColInit);
}
//生成平行轮廓的点
HTuple[] rowCol = null;
GenParallPoint(par.Position, par.DefectType, (int)par.GapIn, (int)par.GapOut, hv_RowInit, hv_ColInit, out rowCol);
hv_Row1 = rowCol[0];
hv_Col1 = rowCol[1];
hv_Row2 = rowCol[2];
hv_Col2 = rowCol[3];
//生成平行轮廓包围的区域
HOperatorSet.TupleInverse(hv_Col2, out hv_InvertedCol);
HOperatorSet.TupleInverse(hv_Row2, out hv_InvertedRow);
HOperatorSet.TupleConcat(hv_Col1, hv_InvertedCol, out hv_ConcatCol);
HOperatorSet.TupleConcat(hv_Row1, hv_InvertedRow, out hv_ConcatRow);
//select_contours_xld (SmoothedContours, SelectedSmoothedContours, 'contour_length', 50, 99999999, -0.5, 0.5)
//HOperatorSet.SelectContoursXld(ho_ContourConcat, out ho_ContourConcat, "contour_length", par.ErrorAreaValue, 99999999, -0.5, 0.5);
if (hv_ConcatRow.Length == 0)
{
result.LevelError_e = LevelError_enum.Error;
result.Annotation = par.NameCell.ToString() + "hv_ConcatRow的数量为0";
result.SetDefault();
return;
}
ho_ContourConcat.Dispose();
HOperatorSet.GenContourPolygonXld(out ho_ContourConcat, hv_ConcatRow, hv_ConcatCol);
//生成平行轮廓region
ho_RegionParall.Dispose();
HOperatorSet.GenRegionContourXld(ho_ContourConcat, out ho_RegionParall, "filled");
ho_ImageParall.Dispose();
HOperatorSet.ReduceDomain(ho_BinImage, ho_RegionParall, out ho_ImageParall);
ho_RegionError.Dispose();
HOperatorSet.Threshold(ho_ImageParall, out ho_RegionError, 100, 255);
ho_ConnectedRegions.Dispose();
HOperatorSet.Connection(ho_RegionError, out ho_ConnectedRegions);
//轮廓的内边界先外移1个像素，再膨胀靠近（忽略最小1个像素的地方）
ho_RegionErosionError.Dispose();
HOperatorSet.SelectShape(ho_ConnectedRegions, out ho_RegionErosionError, "area", "and", par.ErrorAreaValue, 99999999);
//膨胀缺陷
ho_RegionDilationError.Dispose();
HOperatorSet.DilationCircle(ho_RegionErosionError, out ho_RegionDilationError, par.DilationDefectValue);
//剔除残留
HOperatorSet.Difference(ho_RegionDilation, ho_RegionDilationError, out ho_RegionDilation);
HOperatorSet.CountObj(ho_RegionDilationError, out hv_NumberRegionDilation1);
if ((int)(new HTuple(hv_NumberRegionDilation1.TupleEqual(0))) != 0)
{
break;
}
}
//完整图片
ho_BinImage.Dispose();
HOperatorSet.RegionToBin(ho_RegionDilation, out ho_BinImage, 255, 0, hv_Width, hv_Height);
ho_ImageBinReduced.Dispose();
HOperatorSet.ReduceDomain(ho_BinImage, ho_rectErosion1, out ho_ImageBinReduced);
//完整轮廓
ho_BorderFull.Dispose();
HOperatorSet.ThresholdSubPix(ho_ImageBinReduced, out ho_BorderFull, 100);
ho_SmoothedContoursFull.Dispose();
HOperatorSet.SmoothContoursXld(ho_BorderFull, out ho_SmoothedContoursFull, smooth);
HTuple hv_ho_SmoothedContoursFullNumber = null;
HOperatorSet.CountObj(ho_SmoothedContoursFull, out hv_ho_SmoothedContoursFullNumber);//计算平滑区域的xld个数
//如果完整轮廓为空，则返回
if (hv_ho_SmoothedContoursFullNumber == 0)
{
result.LevelError_e = LevelError_enum.Error;
result.Annotation = par.NameCell.ToString() + "ho_SmoothedContoursFull的数量为0";
result.SetDefault();
return;
}
//计算完整轮廓的长度
HTuple hv_SmoothedContoursFullLength = null;
HOperatorSet.LengthXld(ho_SmoothedContoursFull, out hv_SmoothedContoursFullLength);
//找到完整轮廓中最长的一段，剔除干扰小段
HOperatorSet.SelectObj(ho_SmoothedContoursFull, out ho_SmoothedContoursFullLongest, (((hv_SmoothedContoursFullLength.TupleSortIndex()
)).TupleSelect((new HTuple(hv_SmoothedContoursFullLength.TupleLength())) - 1)) + 1);
HTuple[] rowColFull = null;
HOperatorSet.GetContourXld(ho_SmoothedContoursFullLongest, out hv_RowInit, out hv_ColInit);
GenParallPoint(par.Position, par.DefectType, 0, (int)par.GapOut, hv_RowInit, hv_ColInit, out rowColFull);
hv_Row1 = rowColFull[0];
hv_Col1 = rowColFull[1];
hv_Row2 = rowColFull[2];
hv_Col2 = rowColFull[3];
//生成平行轮廓包围的区域
HOperatorSet.TupleInverse(hv_Col2, out hv_InvertedCol);
HOperatorSet.TupleInverse(hv_Row2, out hv_InvertedRow);
HOperatorSet.TupleConcat(hv_Col1, hv_InvertedCol, out hv_ConcatCol);
HOperatorSet.TupleConcat(hv_Row1, hv_InvertedRow, out hv_ConcatRow);
ho_ContourConcat.Dispose();
HOperatorSet.GenContourPolygonXld(out ho_ContourConcat, hv_ConcatRow, hv_ConcatCol);
HOperatorSet.GenRegionContourXld(ho_ContourConcat, out ho_RegionROIFull, "filled");
HOperatorSet.ReduceDomain(ho_ImageBinary, ho_RegionROIFull, out ho_ErrorFull);
ho_FilterErrorFull.Dispose();
ho_FilterInverseROI.Dispose();
if (par.DefectType == "Shell" && parRaisedEdgeSmooth.g_ParROI.g_ParROIExcute_L.Count > 1)
{
ho_FilterROI = funCirROI.CreateOneROI(parRaisedEdgeSmooth.g_ParROI.g_ParROIExcute_L[1], htResult, out blResult, out anno);
HOperatorSet.Complement(ho_FilterROI, out ho_FilterInverseROI);
HOperatorSet.ReduceDomain(ho_ErrorFull, ho_FilterInverseROI, out ho_FilterErrorFull);
}
else
{
ho_FilterErrorFull = ho_ErrorFull.Clone();
}
HOperatorSet.Threshold(ho_FilterErrorFull, out ho_ErrorRegioinFull, 100, 255);
HOperatorSet.Connection(ho_ErrorRegioinFull, out ho_ErrorConnectFull);
HTuple numError = 0;
HTuple rowFull = null;
HTuple colFull = null;
HTuple disMin = null;
HTuple disMax = null;
HTuple disMinSort = null;
HTuple disMinSortIndex = null;
HTuple areaError = null;
HTuple rowError = null;
HTuple colError = null;
HOperatorSet.CountObj(ho_ErrorConnectFull, out numError);
HObject ho_ErrorSelectedPart;
for (int i = 0; i < numError; i++)
{
HOperatorSet.SelectObj(ho_ErrorConnectFull, out ho_ErrorSelectedPart, i + 1);
HOperatorSet.GenContourRegionXld(ho_ErrorSelectedPart, out ho_ErrorXldFull, "border");
HOperatorSet.GetContourXld(ho_ErrorXldFull, out rowFull, out colFull);
HOperatorSet.DistancePc(ho_SmoothedContoursFullLongest, rowFull, colFull, out disMin, out disMax);
HOperatorSet.TupleSort(disMin, out disMinSort);
HOperatorSet.TupleSortIndex(disMin, out disMinSortIndex);
//for (int j = 0; j < disMax.Length; j++)
//{
if (disMinSort[disMinSort.Length - 1] > par.NormalTh)
{
HOperatorSet.AreaCenter(ho_ErrorSelectedPart, out areaError, out rowError, out colError);
result.X_L.Add(colFull[disMinSortIndex[disMinSort.Length - 1].I]);
result.Y_L.Add(rowFull[disMinSortIndex[disMinSort.Length - 1].I]);
result.R_L.Add(0);
double dist = disMinSort[disMinSort.Length - 1];
result.Height_L.Add(Math.Round(dist, 1));
result.Area_L.Add(areaError.ToDArr()[0]);
break;
}
//}
}
//区域个数
result.Num = result.X_L.Count;
if (result.Num == 0)
{
//如果前一次结果为error,那么即使这次的结果是OK，也要保持ERROR的状态
if (result.LevelError_e == LevelError_enum.Error)
{
result.SetDefault();
}
else
{
result.LevelError_e = LevelError_enum.OK;
result.Annotation = par.NameCell.ToString() + "缺陷个数为0";
result.SetDefault();
}
}
//添加显示
AddDisplay(par.g_ParOutput, result);
}
catch (Exception ex)
{
result.LevelError_e = LevelError_enum.Error;
result.Annotation = par.NameCell.ToString() + ex.Message.ToString();
result.SetDefault();
Log.L_I.WriteError(NameClass, ex);
}
finally
{
#region 记录
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ImageBinary", ho_ImageBinary);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ROI", ho_ROI);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_FilterROI", ho_FilterROI);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_rectErosion1", ho_rectErosion1);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ImageReduced", ho_ImageReduced);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_Region", ho_Region);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_RegionDilation", ho_RegionDilation);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_BorderOrigin", ho_BorderOrigin);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ConnectedRegionDilation", ho_ConnectedRegionDilation);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_BinImage", ho_BinImage);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_BorderOriginal", ho_BorderOriginal);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_SmoothedBoaderOriginal", ho_SmoothedBoaderOriginal);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_SelectedSmoothedContours", ho_SelectedSmoothedContours);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ObjectSelected", ho_ObjectSelected);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ContourConcat", ho_ContourConcat);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_RegionParall", ho_RegionParall);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_FilterErrorFull", ho_FilterErrorFull);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ImageParall", ho_ImageParall);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_RegionError", ho_RegionError);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ConnectedRegions", ho_ConnectedRegions);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_RegionErosionError", ho_RegionErosionError);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_RegionDilationError", ho_RegionDilationError);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_BorderFull", ho_BorderFull);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_SmoothedContoursFull", ho_SmoothedContoursFull);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_SmoothedContoursFullLongest", ho_SmoothedContoursFullLongest);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_RegionROIFull", ho_RegionROIFull);
RecordHoject(parRaisedEdgeSmooth, result, NameClass, "ho_ErrorConnectFull", ho_ErrorConnectFull);
#endregion 记录
}
}
public void ProcessStep(HImage imageGrabbed)
{
try
{
HTuple startTime = null;
HTuple endTime = null;
HOperatorSet.CountSeconds(out startTime);
int imageChannels = imageGrabbed.CountChannels();
HImage rImg = null, gImg = null, bImg = null, rgbImg = null, irImg = null;
if (imageChannels == 6)
{
rImg = imageGrabbed.Decompose4(out gImg, out bImg, out irImg);
rgbImg = rImg.Compose3(gImg, bImg);
}
HImage grayImage = new HImage();
if (rgbImg == null)
{
return;
}
imageGrabbed = rgbImg.CopyImage();
int presentImageNoOfChannels = imageGrabbed.CountChannels();
if (presentImageNoOfChannels == Properties.Settings.Default.NumberOfChannelsInColorImage)
{
lock (this.ImageToBeSaved)
{
this.ImageToBeSaved = imageGrabbed.CopyImage();
}
if (whitebalancingStarted)
{
wbIterationCompletedEvent.Reset();
}
imageGrabbedEvent.Set();
HImage ho_R;
HImage ho_G;
HImage ho_B;
ho_R = imageGrabbed.Decompose3(out ho_G, out ho_B);
HTuple RAOIGrayVals = Globals.GetGrayValuesOfLine(ho_R);
HTuple GAOIGrayVals = Globals.GetGrayValuesOfLine(ho_G);
HTuple BAOIGrayVals = Globals.GetGrayValuesOfLine(ho_B);
HTuple IRAOIGrayVals = Globals.GetGrayValuesOfLine(irImg);
currentWBData.Image = imageGrabbed;
currentWBData.GrayValues.RPlaneVals = RAOIGrayVals.ToDArr();
currentWBData.GrayValues.GPlaneVals = GAOIGrayVals.ToDArr();
currentWBData.GrayValues.BPlaneVals = BAOIGrayVals.ToDArr();
currentWBData.GrayValues.MPlaneVals = IRAOIGrayVals.ToDArr();
HImage ho_GrayImage;
ho_GrayImage = imageGrabbed.Rgb1ToGray();
HRegion whiteRegion = ho_GrayImage.Threshold(
Properties.Settings.Default.MinThresholdInDeterminingGain,
Properties.Settings.Default.MaxThresholdInDeterminingGain);
whiteRegion = whiteRegion.FillUp();
whiteRegion = whiteRegion.ErosionRectangle1(20, 20);
double rClipValue = 15.0;
double gClipValue = 15.0;
double bClipValue = 15.0;
//CalculateOptimumClipValue(whiteRegion, ho_R, out rClipValue);
//CalculateOptimumClipValue(whiteRegion, ho_G, out gClipValue);
//CalculateOptimumClipValue(whiteRegion, ho_B, out bClipValue);
double rMin, rMax, rRange;
double gMin, gMax, gRange;
double bMin, bMax, bRange;
ho_R.MinMaxGray(whiteRegion, rClipValue, out rMin, out rMax,
out rRange);
ho_G.MinMaxGray(whiteRegion, gClipValue, out gMin, out gMax,
out gRange);
ho_B.MinMaxGray(whiteRegion, bClipValue, out bMin, out bMax,
out bRange);
double RGDiff = rMax - gMax;
double GBDiff = gMax - bMax;
double BRDiff = bMax - rMax;
currentWBData.ErrorLevel = (Math.Max(RGDiff, Math.Max(GBDiff, BRDiff)) / this.CameraAcquisition.CurrentCameraProperties.BrightRegionReferenceGrayLevel) * 100;
currentWBData.RedMax = rMax;
currentWBData.GreenMax = gMax;
currentWBData.BlueMax = bMax;
HOperatorSet.CountSeconds(out endTime);
currentWBData.TimeTaken = (endTime - startTime).D;
UpdateControlUI();
wbIterationCompletedEvent.WaitOne();
}
}
catch (Exception ex)
{
string errorMessage = "Exception occurred during white balancing step. ";
errorMessage = errorMessage + " Error Message: " + ex.Message;
MessageBox.Show(errorMessage, "Camera Setup Tool", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
