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BoofCV is an open source Java library for real-time computer vision and robotics applications.
/*
* Copyright (c) 2011-2019, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package boofcv.examples.features;
import boofcv.abst.feature.detect.interest.ConfigGeneralDetector;
import boofcv.abst.feature.detect.interest.ConfigShiTomasi;
import boofcv.abst.filter.derivative.ImageGradient;
import boofcv.alg.feature.detect.interest.GeneralFeatureDetector;
import boofcv.factory.feature.detect.interest.FactoryDetectPoint;
import boofcv.factory.filter.derivative.FactoryDerivative;
import boofcv.gui.feature.VisualizeFeatures;
import boofcv.gui.image.ShowImages;
import boofcv.io.UtilIO;
import boofcv.io.image.ConvertBufferedImage;
import boofcv.io.image.UtilImageIO;
import boofcv.struct.QueueCorner;
import boofcv.struct.image.GrayS16;
import boofcv.struct.image.GrayU8;
import georegression.struct.point.Point2D_I16;
import java.awt.*;
import java.awt.image.BufferedImage;
/**
* Example showing how corner features can be detected. These features are not scale invariant, but are
* fast to compute. In OpenCV Shi-Tomasi has the name of goodFeaturesToTrack and uses the unweighted variant.
*
* @author Peter Abeles
*/
public class ExampleCornerFeature {
public static void main(String[] args) {
ConfigGeneralDetector configNonMax = new ConfigGeneralDetector();
// a large radius is used to exaggerate weighted/unweighted affects. Try 1 or 2 for a typical value
configNonMax.radius = 10;
configNonMax.threshold = 100;
configNonMax.maxFeatures = 100;
ConfigShiTomasi configCorner = new ConfigShiTomasi();
configCorner.radius = configNonMax.radius; // in general you should use the same radius here
configCorner.weighted = true; // weighted corners will appear at the corners on a chessboard
// set weighted to false and see what happens to the feature's locations. unweighted is much faster
GeneralFeatureDetector detector = FactoryDetectPoint.createShiTomasi(configNonMax,configCorner, GrayS16.class);
ImageGradient sobel = FactoryDerivative.sobel(GrayU8.class,GrayS16.class);
BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("calibration/mono/Sony_DSC-HX5V_Chess/frame05.jpg"));
// Convert the image into a usable format and predeclare memory
GrayU8 gray = ConvertBufferedImage.convertFrom(image,(GrayU8)null);
GrayS16 derivX = new GrayS16(gray.width,gray.height);
GrayS16 derivY = new GrayS16(gray.width,gray.height);
// The first image derivatives are needed
sobel.process(gray, derivX,derivY);
// Compute the corners
detector.process(gray,derivX,derivY,null,null,null);
// Visualize the results
QueueCorner corners = detector.getMaximums();
Graphics2D g2 = image.createGraphics();
for (int i = 0; i < corners.size; i++) {
Point2D_I16 c = corners.get(i);
VisualizeFeatures.drawPoint(g2,c.x,c.y,4,Color.RED,true);
}
ShowImages.showWindow(image,"Corners",true);
}
}