Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
/*
* Copyright (c) 2021, 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.alg.feature.detect.edge.CannyEdge;
import boofcv.alg.feature.detect.edge.EdgeContour;
import boofcv.alg.feature.detect.edge.EdgeSegment;
import boofcv.alg.filter.binary.BinaryImageOps;
import boofcv.alg.filter.binary.Contour;
import boofcv.alg.filter.binary.ThresholdImageOps;
import boofcv.alg.misc.ImageStatistics;
import boofcv.alg.shapes.ShapeFittingOps;
import boofcv.factory.feature.detect.edge.FactoryEdgeDetectors;
import boofcv.gui.ListDisplayPanel;
import boofcv.gui.feature.VisualizeShapes;
import boofcv.gui.image.ShowImages;
import boofcv.io.UtilIO;
import boofcv.io.image.ConvertBufferedImage;
import boofcv.io.image.UtilImageIO;
import boofcv.struct.ConnectRule;
import boofcv.struct.PointIndex_I32;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.GrayU8;
import georegression.struct.point.Point2D_I32;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.util.List;
import java.util.Random;
/**
* 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 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 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 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 canny =
FactoryEdgeDetectors.canny(2, true, true, GrayF32.class, GrayF32.class);
canny.process(input, 0.1f, 0.3f, null);
List 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 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 canny =
FactoryEdgeDetectors.canny(2, false, true, GrayF32.class, GrayF32.class);
canny.process(input, 0.1f, 0.3f, binary);
// Only external contours are relevant
List 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 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.loadImageNotNull(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);
}
}