How to use

contour

method

in

boofcv.alg.filter.binary.BinaryImageOps

private synchronized void performWork() {
  if( filter1 == null || filter2 == null )
    return;
  GThresholdImageOps.threshold(imageInput, imageBinary, selectThresh.getThreshold(), selectThresh.isDown());
  filter1.process(imageBinary,imageOutput1);
  filter2.process(imageOutput1,imageOutput2);
  List<Contour> found = BinaryImageOps.contour(imageOutput2, connectRule, imageLabeled);
  if( colors == null || colors.length <= found.size() )
    colors = BinaryImageOps.selectRandomColors(found.size(),rand);
  SwingUtilities.invokeLater(new Runnable() {
    public void run() {
      if (work == null || work.getWidth() != imageInput.width || work.getHeight() != imageInput.height) {
        work = new BufferedImage(imageInput.width, imageInput.height, BufferedImage.TYPE_INT_BGR);
      }
      renderVisualizeImage();
      gui.setImage(work);
      gui.setPreferredSize(new Dimension(imageInput.width, imageInput.height));
      processedImage = true;
      gui.repaint();
    }
  });
}

public void process( final GrayU8 input ) {
  // threshold the input image
  inputToBinary.process(input,binary);
  // reduce noise with some filtering
  BinaryImageOps.erode8(binary, 1, filtered);
  BinaryImageOps.dilate8(filtered, 1, binary);
  // Find the contour around the shapes
  contours = BinaryImageOps.contour(binary, ConnectRule.EIGHT,null);
  processImage = true;
  viewUpdated();
}

List<Contour> blobContours = BinaryImageOps.contour(binary, ConnectRule.FOUR, blobs);

public BufferedImage findRoad(BufferedImage src)
{
 // convert into a usable format
 ImageFloat32 input = ConvertBufferedImage.convertFromSingle(src, null, ImageFloat32.class);
 ImageUInt8 binary = new ImageUInt8(input.width, input.height);
 ImageSInt32 blobs = new ImageSInt32(input.width, input.height);
 // the mean pixel value is often a reasonable threshold when creating a binary image
 double mean = ImageStatistics.mean(input);
 // create a binary image
 ThresholdImageOps.threshold(input, binary, (float) mean, true);
 // remove small blobs through erosion and dilation
 // The null in the input indicates that it should internally declare the work image it needs
 // this is less efficient, but easier to code.
 for (int i = 0; i < 1; i++)
 {
   binary = BinaryImageOps.erode8(binary,1, null);
 }
 for (int i = 0; i < 2; i++)
 {
   binary = BinaryImageOps.dilate8(binary,1, null);
 }
 // Detect blobs inside the binary image and assign labels to them
 List<Contour> blobContours = BinaryImageOps.contour(binary, ConnectRule.FOUR, blobs);
 int numBlobs = filterBlobsNotTouchingEdges(blobs, blobContours.size());
 // Render the binary image for output and display it in a window
 BufferedImage dst = VisualizeBinaryData.renderLabeled(blobs, numBlobs, null);
 return dst;
}

  @Override
  public void process(GrayU8 input) {
    // Select a reasonable threshold
    double mean = GThresholdImageOps.computeOtsu(input,0,255);
    // create a binary image by thresholding
    ThresholdImageOps.threshold(input, binary, (int)mean, down);
    // reduce noise with some filtering
    BinaryImageOps.removePointNoise(binary, filtered1);
    // draw binary image for output
    if( showBinary ) {
      VisualizeImageData.binaryToBitmap(filtered1, false, bitmap, bitmapTmp);
    } else {
      ConvertBitmap.boofToBitmap(input,bitmap,bitmapTmp);
    }
    // draw the ellipses
    findContours.process(filtered1,contourOutput);
    List<Contour> contours = BinaryImageOps.contour(filtered1, ConnectRule.EIGHT,null);
    resetShapes();
    for (Contour contour : contours) {
      List<Point2D_I32> points = contour.external;
      if (points.size() < 20)
        continue;
      fitShape(points);
    }
    finalizeShapes();
    visualizationPending = true;
  }
}