Difference between revisions of "Example Fit Polygon"

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Example Code:
Example Code:
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/features/ExampleFitPolygon.java ExampleFitPolygon.java]
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/features/ExampleFitPolygon.java ExampleFitPolygon.java]


Concepts:
Concepts:
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/**
/**
  * Demonstration of how to convert a point sequence describing an objects outline/contour into a sequence of line
  * Demonstration of how to convert a point sequence describing an objects outline/contour into a sequence of line
  * segments. Useful when analysing shapes such as squares and triangles or when trying to simply the low level
  * segments. Useful when analysing shapes such as squares and triangles or when trying to simply the low level
  * pixel output.
  * pixel output.
  *
  *
Line 67: Line 67:


for( Contour c : contours ) {
for( Contour c : contours ) {
// Fit the polygon to the found external contour. Note loop = true
// Fit the polygon to the found external contour. Note loop = true
List<PointIndex_I32> vertexes = ShapeFittingOps.fitPolygon(c.external,true, minSide,cornerPenalty);
List<PointIndex_I32> vertexes = ShapeFittingOps.fitPolygon(c.external,true, minSide,cornerPenalty);


Line 85: Line 85:


/**
/**
* Fits a sequence of line-segments into a sequence of points found using the Canny edge detector. In this case
* Fits a sequence of line-segments into a sequence of points found using the Canny edge detector. In this case
* the points are not connected in a loop. The canny detector produces a more complex tree and the fitted
* the points are not connected in a loop. The canny detector produces a more complex tree and the fitted
* points can be a bit noisy compared to the others.
* points can be a bit noisy compared to the others.
Line 110: Line 110:


for(EdgeSegment s : e.segments ) {
for(EdgeSegment s : e.segments ) {
// fit line segments to the point sequence. Note that loop is false
// fit line segments to the point sequence. Note that loop is false
List<PointIndex_I32> vertexes = ShapeFittingOps.fitPolygon(s.points,false, minSide,cornerPenalty);
List<PointIndex_I32> vertexes = ShapeFittingOps.fitPolygon(s.points,false, minSide,cornerPenalty);


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/**
/**
* Detects contours inside the binary image generated by canny. Only the external contour is relevant. Often
* Detects contours inside the binary image generated by canny. Only the external contour is relevant. Often
* easier to deal with than working with Canny edges directly.
* easier to deal with than working with Canny edges directly.
*/
*/

Revision as of 09:49, 12 July 2021

Demonstration for how to fit a polygon to object contours and edges. The input contours can be found from binary blobs and the edge sequence from Canny edge detector. This is often a useful preprocessing step before applying a higher level image processing algorithm.

Example Code:

Concepts:

  • Object contours/edges
  • Shape fitting

Relevant Videos:

Relevant Examples:

Example Code

/**
 * Demonstration of how to convert a point sequence describing an objects outline/contour into a sequence of line
 * segments. Useful when analysing shapes such as squares and triangles or when trying to simply the low level
 * pixel output.
 *
 * @author Peter Abeles
 */
public class ExampleFitPolygon {

	// Used to bias it towards more or fewer sides. larger number = fewer sides
	static double cornerPenalty = 0.25;
	// The fewest number of pixels a side can have
	static int minSide = 10;

	static ListDisplayPanel gui = new ListDisplayPanel();

	/**
	 * Fits polygons to found contours around binary blobs.
	 */
	public static void fitBinaryImage(GrayF32 input) {

		GrayU8 binary = new GrayU8(input.width,input.height);
		BufferedImage polygon = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);

		// the mean pixel value is often a reasonable threshold when creating a binary image
		double mean = ImageStatistics.mean(input);

		// create a binary image by thresholding
		ThresholdImageOps.threshold(input, binary, (float) mean, true);

		// reduce noise with some filtering
		GrayU8 filtered = BinaryImageOps.erode8(binary, 1, null);
		filtered = BinaryImageOps.dilate8(filtered, 1, null);

		// Find internal and external contour around each shape
		List<Contour> contours = BinaryImageOps.contour(filtered, ConnectRule.EIGHT,null);

		// Fit a polygon to each shape and draw the results
		Graphics2D g2 = polygon.createGraphics();
		g2.setStroke(new BasicStroke(2));

		for( Contour c : contours ) {
			// Fit the polygon to the found external contour. Note loop = true
			List<PointIndex_I32> vertexes = ShapeFittingOps.fitPolygon(c.external,true, minSide,cornerPenalty);

			g2.setColor(Color.RED);
			VisualizeShapes.drawPolygon(vertexes,true,g2);

			// handle internal contours now
			g2.setColor(Color.BLUE);
			for( List<Point2D_I32> internal : c.internal ) {
				vertexes = ShapeFittingOps.fitPolygon(internal,true, minSide,cornerPenalty);
				VisualizeShapes.drawPolygon(vertexes,true,g2);
			}
		}

		gui.addImage(polygon, "Binary Blob Contours");
	}

	/**
	 * Fits a sequence of line-segments into a sequence of points found using the Canny edge detector. In this case
	 * the points are not connected in a loop. The canny detector produces a more complex tree and the fitted
	 * points can be a bit noisy compared to the others.
	 */
	public static void fitCannyEdges( GrayF32 input ) {

		BufferedImage displayImage = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);

		// Finds edges inside the image
		CannyEdge<GrayF32,GrayF32> canny =
				FactoryEdgeDetectors.canny(2, true, true, GrayF32.class, GrayF32.class);

		canny.process(input,0.1f,0.3f,null);
		List<EdgeContour> contours = canny.getContours();

		Graphics2D g2 = displayImage.createGraphics();
		g2.setStroke(new BasicStroke(2));

		// used to select colors for each line
		Random rand = new Random(234);

		for( EdgeContour e : contours ) {
			g2.setColor(new Color(rand.nextInt()));

			for(EdgeSegment s : e.segments ) {
				// fit line segments to the point sequence. Note that loop is false
				List<PointIndex_I32> vertexes = ShapeFittingOps.fitPolygon(s.points,false, minSide,cornerPenalty);

				VisualizeShapes.drawPolygon(vertexes, false, g2);
			}
		}

		gui.addImage(displayImage, "Canny Trace");
	}

	/**
	 * Detects contours inside the binary image generated by canny. Only the external contour is relevant. Often
	 * easier to deal with than working with Canny edges directly.
	 */
	public static void fitCannyBinary( GrayF32 input ) {

		BufferedImage displayImage = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);
		GrayU8 binary = new GrayU8(input.width,input.height);

		// Finds edges inside the image
		CannyEdge<GrayF32,GrayF32> canny =
				FactoryEdgeDetectors.canny(2, false, true, GrayF32.class, GrayF32.class);

		canny.process(input,0.1f,0.3f,binary);

		// Only external contours are relevant
		List<Contour> contours = BinaryImageOps.contourExternal(binary, ConnectRule.EIGHT);

		Graphics2D g2 = displayImage.createGraphics();
		g2.setStroke(new BasicStroke(2));

		// used to select colors for each line
		Random rand = new Random(234);

		for( Contour c : contours ) {
			List<PointIndex_I32> vertexes = ShapeFittingOps.fitPolygon(c.external,true, minSide,cornerPenalty);

			g2.setColor(new Color(rand.nextInt()));
			VisualizeShapes.drawPolygon(vertexes,true,g2);
		}

		gui.addImage(displayImage, "Canny Contour");
	}

	public static void main( String[] args ) {
		// load and convert the image into a usable format
		BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("shapes/shapes02.png"));
		GrayF32 input = ConvertBufferedImage.convertFromSingle(image, null, GrayF32.class);

		fitCannyEdges(input);
		fitCannyBinary(input);
		fitBinaryImage(input);
		gui.addImage(image,"Original");

		ShowImages.showWindow(gui, "Polygon from Contour", true);
	}
}