/////////////////////////////////////////////////////////////////////////////////
///
/// Function Name: IVA_GetPoint
///
/// Description : Retrieves a point from the PointsResults array
///
/// Parameters : ivaData - Internal data structure
/// stepIndex - Index of the step that produced the point
/// pointIndex - Index of the x value.
///
/// Return Value : point
///
/////////////////////////////////////////////////////////////////////////////////
public static PointContour IVA_GetPoint(IVA_Data ivaData, int stepIndex, int pointIndex)
{
PointContour point = new PointContour();
if ((pointIndex + 1) < ivaData.stepResults[stepIndex].results.Count)
{
point.X = ivaData.stepResults[stepIndex].results[pointIndex].resultVal.numVal;
point.Y = ivaData.stepResults[stepIndex].results[pointIndex + 1].resultVal.numVal;
}
return(point);
}
/////////////////////////////////////////////////////////////////////////////////
///
/// Function Name: IVA_PushBuffer
///
/// Description : Stores an image in a buffer
///
/// Parameters : ivaData - Internal data structure
/// image - image
/// bufferNumber - Buffer index
///
/// Return Value : success
///
/////////////////////////////////////////////////////////////////////////////////
public static void IVA_PushBuffer(IVA_Data ivaData, VisionImage image, int bufferNumber)
{
/// Release the previous image that was contained in the buffer
ivaData.buffers[bufferNumber].Dispose();
/// Creates an image buffer of the same type of the source image.
ivaData.buffers[bufferNumber] = new VisionImage(image.Type, 7);
/// Copies the image in the buffer.
Algorithms.Copy(image, ivaData.buffers[bufferNumber]);
}
/////////////////////////////////////////////////////////////////////////////////
///
/// Function Name: IVA_GetNumericResult
///
/// Description : Retrieves a numeric result value from the data manager.
///
/// Parameters : ivaData - Internal data structure
/// stepIndex - Index of the step that produced the result
/// resultIndex - result index.
///
/// Return Value : numeric result value
///
/////////////////////////////////////////////////////////////////////////////////
public static double IVA_GetNumericResult(IVA_Data ivaData, int stepIndex, int resultIndex)
{
double value = 0;
if (resultIndex < ivaData.stepResults[stepIndex].results.Count)
{
value = ivaData.stepResults[stepIndex].results[resultIndex].resultVal.numVal;
}
return(value);
}
public PaletteType ProcessImage(VisionImage image)
{
// Initialize the IVA_Data structure to pass results and coordinate systems.
IVA_Data ivaData = new IVA_Data(7, 0);
// Extract Color Plane
using (VisionImage plane = new VisionImage(ImageType.U8, 7))
{
// Extract the red color plane and copy it to the main image.
Algorithms.ExtractColorPlanes(image, ColorMode.Rgb, plane, null, null);
Algorithms.Copy(plane, image);
}
// Filters: Convolution - Applies a linear filter to an image by convolving the image with a filtering kernel.
double[] vaCoefficients = { 1, 2, 4, 2, 1, 2, 4, 8, 4, 2, 4, 8, 16, 8, 4, 2, 4, 8, 4, 2, 1, 2, 4, 2, 1 };
Algorithms.Convolute(image, image, new Kernel(5, 5, vaCoefficients));
// Filters: Convolution - Applies a linear filter to an image by convolving the image with a filtering kernel.
double[] vaCoefficients2 = { -1, -1, -1, -1, 10, -1, -1, -1, -1 };
Algorithms.Convolute(image, image, new Kernel(3, 3, vaCoefficients2));
// Automatic Threshold
Algorithms.AutoThreshold(image, image, 2, ThresholdMethod.Clustering);
// Basic Morphology - Applies morphological transformations to binary images.
int[] vaCoefficients3 = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
StructuringElement vaStructElem = new StructuringElement(7, 7, vaCoefficients3);
vaStructElem.Shape = StructuringElementShape.Hexagon;
// Applies morphological transformations
Algorithms.Morphology(image, image, MorphologyMethod.Open, vaStructElem);
// Lookup Table: Equalize
// Calculates the histogram of the image and redistributes pixel values
// accross the desired range to maintain the same pixel value distribution.
Range equalizeRange = new Range(0, 255);
if (image.Type != ImageType.U8)
{
equalizeRange.Maximum = 0;
}
Algorithms.Equalize(image, image, null, equalizeRange, null);
// Creates a new, empty region of interest.
Roi roi = new Roi();
// Creates a new RectangleContour using the given values.
RectangleContour vaRect = new RectangleContour(0, 0, image.Width, image.Height);
roi.Add(vaRect);
// Classifies all the objects located in the given ROI.
string vaClassifierFilePath = "C:\\DATA\\#hasilscan2\\Ukuran Classifier.clf";
vaClassifierReports = IVA_Classify(image, roi, vaClassifierFilePath);
roi.Dispose();
// Dispose the IVA_Data structure.
ivaData.Dispose();
// Return the palette type of the final image.
return(PaletteType.Binary);
}
/////////////////////////////////////////////////////////////////////////////////
///
/// Function Name: IVA_PopBuffer
///
/// Description : Retrieves an image from a buffer
///
/// Parameters : ivaData - Internal data structure
/// bufferNumber - Buffer index
///
/// Return Value : success
///
/////////////////////////////////////////////////////////////////////////////////
public static VisionImage IVA_GetBuffer(IVA_Data ivaData, int bufferNumber)
{
return(ivaData.buffers[bufferNumber]);
}
/////////////////////////////////////////////////////////////////////////////////
///
/// Function Name: IVA_DisposeStepResults
///
/// Description : Dispose of the results of a specific step.
///
/// Parameters : ivaData - Internal data structure
/// stepIndex - step index
///
/// Return Value : success
///
/////////////////////////////////////////////////////////////////////////////////
public static void IVA_DisposeStepResults(IVA_Data ivaData, int stepIndex)
{
ivaData.stepResults[stepIndex].results.Clear();
}
