Difference between revisions of "Example Detect Lines"

From BoofCV
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m
 
Line 11: Line 11:
  
 
Example Code:
 
Example Code:
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.32/examples/src/boofcv/examples/features/ExampleLineDetection.java ExampleLineDetection.java]
+
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.34/examples/src/boofcv/examples/features/ExampleLineDetection.java ExampleLineDetection.java]
  
 
Concepts:
 
Concepts:
Line 35: Line 35:
 
* Detects lines inside the image using different types of Hough detectors
 
* Detects lines inside the image using different types of Hough detectors
 
*
 
*
* @param image Input image.
+
* @param buffered Input image.
 
* @param imageType Type of image processed by line detector.
 
* @param imageType Type of image processed by line detector.
* @param derivType Type of image derivative.
 
 
*/
 
*/
public static<T extends ImageGray<T>, D extends ImageGray<D>>
+
public static<T extends ImageGray<T>>
void detectLines( BufferedImage image ,  
+
void detectLines( BufferedImage buffered , Class<T> imageType )
  Class<T> imageType ,
 
  Class<D> derivType )
 
 
{
 
{
 
// convert the line into a single band image
 
// convert the line into a single band image
T input = ConvertBufferedImage.convertFromSingle(image, null, imageType );
+
T input = ConvertBufferedImage.convertFromSingle(buffered, null, imageType );
 +
T blurred = input.createSameShape();
 +
 
 +
// Blur smooths out gradient and improves results
 +
GBlurImageOps.gaussian(input,blurred,0,5,null);
 +
 
 +
// Detect edges of objects using gradient based hough detectors. If you have nice binary lines which are thin
 +
// there's another type of hough detector available
 +
DetectLine<T> detectorPolar = FactoryDetectLine.houghLinePolar(
 +
new ConfigHoughGradient(maxLines),null, imageType);
 +
DetectLine<T> detectorFoot = FactoryDetectLine.houghLineFoot(
 +
new ConfigHoughGradient(maxLines),null, imageType);
 +
DetectLine<T> detectorFootSub = FactoryDetectLine.houghLineFootSub(
 +
new ConfigHoughFootSubimage(3, 8, 5, edgeThreshold,maxLines, 2, 2), imageType);
  
// Comment/uncomment to try a different type of line detector
+
detectLines(buffered,blurred,detectorPolar,"Hough Polar");
DetectLineHoughPolar<T,D> detector = FactoryDetectLineAlgs.houghPolar(
+
detectLines(buffered,blurred,detectorFoot,"Hough Foot");
new ConfigHoughPolar(3, 30, 2, Math.PI / 180,edgeThreshold, maxLines), imageType, derivType);
+
detectLines(buffered,blurred,detectorFootSub,"Hough Foot-Sub");
// DetectLineHoughFoot<T,D> detector = FactoryDetectLineAlgs.houghFoot(
+
}
// new ConfigHoughFoot(3, 8, 5, edgeThreshold,maxLines), imageType, derivType);
 
// DetectLineHoughFootSubimage<T,D> detector = FactoryDetectLineAlgs.houghFootSub(
 
// new ConfigHoughFootSubimage(3, 8, 5, edgeThreshold,maxLines, 2, 2), imageType, derivType);
 
  
List<LineParametric2D_F32> found = detector.detect(input);
+
private static <T extends ImageGray<T>>
 +
void detectLines( BufferedImage buffered, T gray , DetectLine<T> detector , String name ) {
 +
List<LineParametric2D_F32> found = detector.detect(gray);
  
 
// display the results
 
// display the results
 
ImageLinePanel gui = new ImageLinePanel();
 
ImageLinePanel gui = new ImageLinePanel();
gui.setImage(image);
+
gui.setImage(buffered);
 
gui.setLines(found);
 
gui.setLines(found);
gui.setPreferredSize(new Dimension(image.getWidth(),image.getHeight()));
+
gui.setPreferredSize(new Dimension(gray.getWidth(),gray.getHeight()));
  
listPanel.addItem(gui, "Found Lines");
+
listPanel.addItem(gui, name);
 
}
 
}
  
Line 71: Line 80:
 
* @param image Input image.
 
* @param image Input image.
 
* @param imageType Type of image processed by line detector.
 
* @param imageType Type of image processed by line detector.
* @param derivType Type of image derivative.
 
 
*/
 
*/
 
public static<T extends ImageGray<T>, D extends ImageGray<D>>
 
public static<T extends ImageGray<T>, D extends ImageGray<D>>
 
void detectLineSegments( BufferedImage image ,
 
void detectLineSegments( BufferedImage image ,
Class<T> imageType ,
+
Class<T> imageType )
Class<D> derivType )
 
 
{
 
{
 
// convert the line into a single band image
 
// convert the line into a single band image
Line 82: Line 89:
  
 
// Comment/uncomment to try a different type of line detector
 
// Comment/uncomment to try a different type of line detector
DetectLineSegmentsGridRansac<T,D> detector = FactoryDetectLineAlgs.lineRansac(40, 30, 2.36, true, imageType, derivType);
+
DetectLineSegment<T> detector = FactoryDetectLine.lineRansac(new ConfigLineRansac(40, 30, 2.36, true), imageType);
  
 
List<LineSegment2D_F32> found = detector.detect(input);
 
List<LineSegment2D_F32> found = detector.detect(input);
Line 92: Line 99:
 
gui.setPreferredSize(new Dimension(image.getWidth(),image.getHeight()));
 
gui.setPreferredSize(new Dimension(image.getWidth(),image.getHeight()));
  
listPanel.addItem(gui, "Found Line Segments");
+
listPanel.addItem(gui, "Line Segments");
 
}
 
}
 
 
Line 98: Line 105:
 
BufferedImage input = UtilImageIO.loadImage(UtilIO.pathExample("simple_objects.jpg"));
 
BufferedImage input = UtilImageIO.loadImage(UtilIO.pathExample("simple_objects.jpg"));
  
detectLines(input, GrayU8.class, GrayS16.class);
+
detectLines(input, GrayU8.class);
  
 
// line segment detection is still under development and only works for F32 images right now
 
// line segment detection is still under development and only works for F32 images right now
detectLineSegments(input, GrayF32.class, GrayF32.class);
+
detectLineSegments(input, GrayF32.class);
  
 
ShowImages.showWindow(listPanel, "Detected Lines", true);
 
ShowImages.showWindow(listPanel, "Detected Lines", true);

Latest revision as of 11:16, 7 July 2019

Lines are commonly found in man made environments. They can often be detected in location where other feature cannot due to the environments sparsity. Typical applications are for location targets and for evaluating the 3D structure of a building. Mathematically, a line has no end points and a line detector in BoofCV does not detect end points either. BoofCV does provide ways to detect line segments, which are lines with a beginning and end.

Line and line segment detection is still under development. No highly abstract and simplified interface is provided yet. Even though its under development still, these algorithms are still effective at detecting lines and line segments.

Example Code:

Concepts:

  • Line detection
  • Line segment detection

Relevant Examples:

Example Code

public class ExampleLineDetection {

	// adjusts edge threshold for identifying pixels belonging to a line
	private static final float edgeThreshold = 25;
	// adjust the maximum number of found lines in the image
	private static final int maxLines = 10;

	private static ListDisplayPanel listPanel = new ListDisplayPanel();

	/**
	 * Detects lines inside the image using different types of Hough detectors
	 *
	 * @param buffered Input image.
	 * @param imageType Type of image processed by line detector.
	 */
	public static<T extends ImageGray<T>>
	void detectLines( BufferedImage buffered , Class<T> imageType )
	{
		// convert the line into a single band image
		T input = ConvertBufferedImage.convertFromSingle(buffered, null, imageType );
		T blurred = input.createSameShape();

		// Blur smooths out gradient and improves results
		GBlurImageOps.gaussian(input,blurred,0,5,null);

		// Detect edges of objects using gradient based hough detectors. If you have nice binary lines which are thin
		// there's another type of hough detector available
		DetectLine<T> detectorPolar = FactoryDetectLine.houghLinePolar(
				new ConfigHoughGradient(maxLines),null, imageType);
		DetectLine<T> detectorFoot = FactoryDetectLine.houghLineFoot(
				new ConfigHoughGradient(maxLines),null, imageType);
		DetectLine<T> detectorFootSub = FactoryDetectLine.houghLineFootSub(
				new ConfigHoughFootSubimage(3, 8, 5, edgeThreshold,maxLines, 2, 2), imageType);

		detectLines(buffered,blurred,detectorPolar,"Hough Polar");
		detectLines(buffered,blurred,detectorFoot,"Hough Foot");
		detectLines(buffered,blurred,detectorFootSub,"Hough Foot-Sub");
	}

	private static <T extends ImageGray<T>>
	void detectLines( BufferedImage buffered, T gray , DetectLine<T> detector , String name ) {
		List<LineParametric2D_F32> found = detector.detect(gray);

		// display the results
		ImageLinePanel gui = new ImageLinePanel();
		gui.setImage(buffered);
		gui.setLines(found);
		gui.setPreferredSize(new Dimension(gray.getWidth(),gray.getHeight()));

		listPanel.addItem(gui, name);
	}

	/**
	 * Detects segments inside the image
	 *
	 * @param image Input image.
	 * @param imageType Type of image processed by line detector.
	 */
	public static<T extends ImageGray<T>, D extends ImageGray<D>>
	void detectLineSegments( BufferedImage image ,
							 Class<T> imageType )
	{
		// convert the line into a single band image
		T input = ConvertBufferedImage.convertFromSingle(image, null, imageType );

		// Comment/uncomment to try a different type of line detector
		DetectLineSegment<T> detector = FactoryDetectLine.lineRansac(new ConfigLineRansac(40, 30, 2.36, true), imageType);

		List<LineSegment2D_F32> found = detector.detect(input);

		// display the results
		ImageLinePanel gui = new ImageLinePanel();
		gui.setImage(image);
		gui.setLineSegments(found);
		gui.setPreferredSize(new Dimension(image.getWidth(),image.getHeight()));

		listPanel.addItem(gui, "Line Segments");
	}
	
	public static void main( String args[] ) {
		BufferedImage input = UtilImageIO.loadImage(UtilIO.pathExample("simple_objects.jpg"));

		detectLines(input, GrayU8.class);

		// line segment detection is still under development and only works for F32 images right now
		detectLineSegments(input, GrayF32.class);

		ShowImages.showWindow(listPanel, "Detected Lines", true);
	}
}