Example Calibrate Planar Mono

• 

  Left uncalibrated. Right calibrated with lens distortion removed. Numbers are super imposed on the image to show calibration points.

This example demonstrates how to use a high level calibration class that automatically detects calibration targets as viewed from a single (monocular) camera in a set of images. After processing the images the intrinsic camera parameters and lens distortion are saved to an XML file. Both the square grid and chessboard patterns are supported by this example. For a full description of the calibration process and instruction on how to do it yourself see the tutorial linked to below.

Example File: ExampleCalibrateMonocular.java

Calibration Tutorial: Wikipage

Concepts:

• Camera calibration
• Lens distortion
• Intrinsic parameters

Related Examples:

• Stereo Camera Calibration
• Removing Lens Distortion

Example Code

/**
 * Example of how to calibrate a single (monocular) camera using a high level interface that processes images of planar
 * calibration targets.  The entire calibration target must be observable in the image and for best results images
 * should be in focus and not blurred.  For a lower level example of camera calibration which processes a set of
 * observed calibration points see {@link ExampleCalibrateMonocular}.
 *
 * After processing both intrinsic camera parameters and lens distortion are estimated.  Square grid and chessboard
 * targets are demonstrated by this example. See calibration tutorial for a discussion of different target types
 * and how to collect good calibration images.
 *
 * All the image processing and calibration is taken care of inside of {@link CalibrateMonoPlanar}.  The code below
 * loads calibration images as inputs, calibrates, and saves results to an XML file.  See in code comments for tuning
 * and implementation issues.
 *
 * @see CalibrateMonoPlanar
 *
 * @author Peter Abeles
 */
public class ExampleCalibrateMonocular {
	public static void main( String args[] ) {
		DetectorFiducialCalibration detector;
		List<String> images;

		// Asymmetric Circle Example
//		detector = FactoryFiducialCalibration.circleAsymmGrid(new ConfigCircleAsymmetricGrid(5, 8, 1, 6));
//		images = BoofMiscOps.directoryList(UtilIO.pathExample("calibration/mono/Sony_DSC-HX5V_CircleAsym"),"image");

		// Square Grid example
//		detector = FactoryFiducialCalibration.squareGrid(new ConfigSquareGrid(4, 3, 30, 30));
//		images = BoofMiscOps.directoryList(UtilIO.pathExample("calibration/stereo/Bumblebee2_Square"),"left");

		// Chessboard Example
		detector = FactoryFiducialCalibration.chessboard(new ConfigChessboard(7, 5, 30));
		images = BoofMiscOps.directoryList(UtilIO.pathExample("calibration/stereo/Bumblebee2_Chess"),"left");

		// Declare and setup the calibration algorithm
		CalibrateMonoPlanar calibrationAlg = new CalibrateMonoPlanar(detector);

		// tell it type type of target and which parameters to estimate
		calibrationAlg.configure( true, 2, false);

		for( String n : images ) {
			BufferedImage input = UtilImageIO.loadImage(n);
			if( n != null ) {
				GrayF32 image = ConvertBufferedImage.convertFrom(input,(GrayF32)null);
				if( !calibrationAlg.addImage(image) )
					System.err.println("Failed to detect target in "+n);
			}
		}
		// process and compute intrinsic parameters
		CameraPinholeRadial intrinsic = calibrationAlg.process();

		// save results to a file and print out
		CalibrationIO.save(intrinsic, "intrinsic.yaml");

		calibrationAlg.printStatistics();
		System.out.println();
		System.out.println("--- Intrinsic Parameters ---");
		System.out.println();
		intrinsic.print();
	}
}