001/*******************************************************************************
002 * This software is provided as a supplement to the authors' textbooks on digital
003 * image processing published by Springer-Verlag in various languages and editions.
004 * Permission to use and distribute this software is granted under the BSD 2-Clause
005 * "Simplified" License (see http://opensource.org/licenses/BSD-2-Clause).
006 * Copyright (c) 2006-2023 Wilhelm Burger, Mark J. Burge. All rights reserved.
007 * Visit https://imagingbook.com for additional details.
008 ******************************************************************************/
009
010package Ch25_SIFT;
011
012import ij.IJ;
013import ij.ImagePlus;
014import ij.gui.GenericDialog;
015import ij.plugin.filter.PlugInFilter;
016import ij.process.FloatProcessor;
017import ij.process.ImageProcessor;
018import imagingbook.common.ij.DialogUtils;
019import imagingbook.common.ij.IjUtils;
020import imagingbook.common.ij.overlay.ColoredStroke;
021import imagingbook.common.ij.overlay.ShapeOverlayAdapter;
022import imagingbook.common.sift.SiftColors;
023import imagingbook.common.sift.SiftDescriptor;
024import imagingbook.common.sift.SiftDetector;
025import imagingbook.common.sift.SiftParameters;
026import imagingbook.core.jdoc.JavaDocHelp;
027import imagingbook.core.resource.ImageResource;
028import imagingbook.sampleimages.GeneralSampleImage;
029
030import java.awt.Color;
031import java.util.List;
032
033import static imagingbook.common.color.sets.ColorEnumeration.getColors;
034
035/**
036 * <p>
037 * This plugin extracts multi-scale SIFT features [1] from the current image and displays them as M-shaped markers. The
038 * list of keypoints (if shown) is sorted by descending magnitude. The input image is always converted to grayscale
039 * before SIFT feature detection is performed. See Ch. 25 of [2] for details. If no image is currently open, the user is
040 * asked to load a predefined sample image.
041 * </p>
042 * <p>
043 * [1] D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision
044 * 60, 91–110 (2004). <br> [2] W. Burger, M.J. Burge, <em>Digital Image Processing &ndash; An Algorithmic
045 * Introduction</em>, 3rd ed, Springer (2022).
046 * </p>
047 *
048 * @author WB
049 * @version 2022/04/01
050 * @see SiftDetector
051 * @see SiftDescriptor
052 */
053
054public class SIFT_Detection_Demo implements PlugInFilter, JavaDocHelp {
055
056        private static ImageResource SampleImage = GeneralSampleImage.Castle;
057        private static SiftParameters params = new SiftParameters();
058        private static int MaxFeaturesToShow = 200;
059        private static double FeatureScale = 1.0; // 1.5;
060        private static double FeatureStrokewidth = 0.5;
061        private static boolean ListSiftFeatures = false;
062        private static Color[] ScaleLevelColors = getColors(SiftColors.class);
063        
064        private ImagePlus im;
065
066        /**
067         * Constructor, asks to open a predefined sample image if no other image is currently open.
068         */
069        public SIFT_Detection_Demo() {
070                if (IjUtils.noCurrentImage()) {
071                        DialogUtils.askForSampleImage(SampleImage);
072                }
073        }
074        
075        // ---------------------------------------------------
076        
077        @Override
078        public int setup(String arg0, ImagePlus im) {
079                this.im = im;
080                return DOES_ALL;
081        }
082
083        @Override
084        public void run(ImageProcessor ip) {            
085                if (!runDialog()) {
086                        return;
087                }
088                
089                FloatProcessor fp = ip.convertToFloatProcessor();
090                SiftDetector detector = new SiftDetector(fp, params);
091                List<SiftDescriptor> features = detector.getSiftFeatures();
092                
093                ColoredStroke[] fStrokes = new ColoredStroke[ScaleLevelColors.length];
094                for (int i = 0; i < ScaleLevelColors.length; i++) {
095                        fStrokes[i] = new ColoredStroke(FeatureStrokewidth, ScaleLevelColors[i]);
096                }
097                
098                ShapeOverlayAdapter ola = new ShapeOverlayAdapter();
099                
100                int cnt = 1;
101                for (SiftDescriptor sf : features) {    
102                        ColoredStroke stroke = fStrokes[sf.getScaleLevel() % fStrokes.length];
103                        ola.addShape(sf.getShape(FeatureScale), stroke);
104                        if(++cnt > MaxFeaturesToShow) break;
105                }
106
107                im.setOverlay(ola.getOverlay());
108                
109                if (ListSiftFeatures) {
110                        int n = 1;
111                        for (SiftDescriptor sf : features) {
112                                IJ.log(n + ": " + sf.toString());
113                                if(++n > MaxFeaturesToShow) break;
114                        }
115                }
116        }
117        
118        // ---------------------------------------------------
119        
120        private boolean runDialog() {
121                GenericDialog gd = new GenericDialog(this.getClass().getSimpleName());
122                gd.addHelp(getJavaDocUrl());
123                DialogUtils.addToDialog(params, gd);
124                gd.addNumericField("Max. number of features to show", MaxFeaturesToShow);
125                gd.addCheckbox("List SIFT features)", ListSiftFeatures);
126                
127                gd.showDialog();
128                if (gd.wasCanceled()) {
129                        return false;
130                }
131                
132                DialogUtils.getFromDialog(params, gd);
133                MaxFeaturesToShow = (int) gd.getNextNumber();
134                ListSiftFeatures = gd.getNextBoolean();
135                return true;
136        }
137
138}