001/** 002 * Copyright (c) 2011, The University of Southampton and the individual contributors. 003 * All rights reserved. 004 * 005 * Redistribution and use in source and binary forms, with or without modification, 006 * are permitted provided that the following conditions are met: 007 * 008 * * Redistributions of source code must retain the above copyright notice, 009 * this list of conditions and the following disclaimer. 010 * 011 * * Redistributions in binary form must reproduce the above copyright notice, 012 * this list of conditions and the following disclaimer in the documentation 013 * and/or other materials provided with the distribution. 014 * 015 * * Neither the name of the University of Southampton nor the names of its 016 * contributors may be used to endorse or promote products derived from this 017 * software without specific prior written permission. 018 * 019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND 020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR 023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 029 */ 030package org.openimaj.demos.acmmm11.presentation.slides.tutorial; 031 032import org.openimaj.image.MBFImage; 033import org.openimaj.image.colour.ColourSpace; 034import org.openimaj.ml.clustering.FloatCentroidsResult; 035import org.openimaj.ml.clustering.assignment.hard.ExactFloatAssigner; 036import org.openimaj.ml.clustering.kmeans.FloatKMeans; 037import org.openimaj.video.Video; 038 039/** 040 * Slide showing segmentation using k-means clustering 041 * 042 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk) 043 * @author Sina Samangooei (ss@ecs.soton.ac.uk) 044 * 045 */ 046 047public class SegmentationTutorial extends TutorialPanel { 048 private static final long serialVersionUID = 1L; 049 050 private FloatCentroidsResult cluster; 051 052 /** 053 * Default constructor 054 * 055 * @param capture 056 * @param width 057 * @param height 058 */ 059 public SegmentationTutorial(Video<MBFImage> capture, int width, int height) { 060 super("Posterisation with K-Means", capture, width, height); 061 } 062 063 @Override 064 public void doTutorial(MBFImage toDraw) { 065 final MBFImage space = ColourSpace.convert(toDraw, ColourSpace.CIE_Lab); 066 067 if (cluster == null) 068 cluster = clusterPixels(space); 069 070 if (cluster == null) 071 return; 072 073 final float[][] centroids = cluster.getCentroids(); 074 075 final ExactFloatAssigner assigner = new ExactFloatAssigner(cluster); 076 077 for (int y = 0; y < space.getHeight(); y++) { 078 for (int x = 0; x < space.getWidth(); x++) { 079 final float[] pixel = space.getPixelNative(x, y); 080 final int centroid = assigner.assign(pixel); 081 space.setPixelNative(x, y, centroids[centroid]); 082 } 083 } 084 085 toDraw.internalAssign(ColourSpace.convert(space, ColourSpace.RGB)); 086 } 087 088 private FloatCentroidsResult clusterPixels(MBFImage toDraw) { 089 final float[][] testP = toDraw.getBand(0).pixels; 090 float sum = 0; 091 092 for (int i = 0; i < testP.length; i++) 093 for (int j = 0; j < testP[i].length; j++) 094 sum += testP[i][j]; 095 096 if (sum == 0) 097 return null; 098 099 final FloatKMeans k = FloatKMeans.createExact(3, 2); 100 final float[][] imageData = toDraw.getPixelVectorNative(new float[toDraw.getWidth() * toDraw.getHeight() * 3][3]); 101 102 return k.cluster(imageData); 103 } 104}