Example Fiducial Square Image

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Demonstration how to detect square image fiducials. After the fiducial detector has been created a description of each image it detects is passed in. These images are converted into binary images and resized if needed. A large number of unique fiducials can be detected with a linear growth in computational time.

Example Code:

Concepts:

  • Fiducials
  • Pose estimation

Relevant Examples/Tutorials:

Relevant Applets:

Example Code

/**
 * Detects square binary fiducials inside an image, writes out there pose, and visualizes a virtual flat cube
 * above them in the input image.
 *
 * @author Peter Abeles
 */
public class ExampleFiducialImage {
	public static void main(String[] args) {

		String imagePath   = "../data/applet/fiducial/image/examples/";
		String patternPath = "../data/applet/fiducial/image/patterns/";

		String imageName = "image00.jpg";
//		String imageName = "image01.jpg";
//		String imageName = "image02.jpg";

		// load the lens distortion parameters and the input image
		IntrinsicParameters param = UtilIO.loadXML(imagePath + "intrinsic.xml");
		BufferedImage input = loadImage(imagePath + imageName);
		ImageFloat32 original = ConvertBufferedImage.convertFrom(input, true, ImageType.single(ImageFloat32.class));

		// Detect the fiducial
		SquareImage_to_FiducialDetector<ImageFloat32> detector = FactoryFiducial.
				squareImageRobust(new ConfigFiducialImage(), 6, ImageFloat32.class);
//				squareImageFast(new ConfigFiducialImage(0.1), 100, ImageFloat32.class);

		// give it a description of all the targets
		double width = 4; // 4 cm
		detector.addPatternImage(loadImage(patternPath + "ke.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "dog.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "yu.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "yu_inverted.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "pentarose.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "text_boofcv.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "leaf01.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "leaf02.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "hand01.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "chicken.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "h2o.png", ImageFloat32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath + "yinyang.png", ImageFloat32.class), 100, width);

		detector.setIntrinsic(param);

		detector.detect(original);

		// print the results
		Graphics2D g2 = input.createGraphics();
		Se3_F64 targetToSensor = new Se3_F64();
		for (int i = 0; i < detector.totalFound(); i++) {
			System.out.println("Target ID = "+detector.getId(i));
			detector.getFiducialToCamera(i, targetToSensor);
			System.out.println("Location:");
			System.out.println(targetToSensor);

			VisualizeFiducial.drawNumbers(targetToSensor,param,detector.getId(i), g2);
			VisualizeFiducial.drawCube(targetToSensor,param,detector.getWidth(i), 3, g2);
		}

		ShowImages.showWindow(input,"Fiducials",true);

	}
}