1 /** 2 * Copyright (c) 2011, The University of Southampton and the individual contributors. 3 * All rights reserved. 4 * 5 * Redistribution and use in source and binary forms, with or without modification, 6 * are permitted provided that the following conditions are met: 7 * 8 * * Redistributions of source code must retain the above copyright notice, 9 * this list of conditions and the following disclaimer. 10 * 11 * * Redistributions in binary form must reproduce the above copyright notice, 12 * this list of conditions and the following disclaimer in the documentation 13 * and/or other materials provided with the distribution. 14 * 15 * * Neither the name of the University of Southampton nor the names of its 16 * contributors may be used to endorse or promote products derived from this 17 * software without specific prior written permission. 18 * 19 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND 20 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 21 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 22 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR 23 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 24 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 25 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 26 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 27 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 28 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 29 */ 30 package org.openimaj.image.model.patch; 31 32 import org.openimaj.feature.DoubleFVComparison; 33 import org.openimaj.image.MBFImage; 34 import org.openimaj.image.pixel.statistics.HistogramModel; 35 36 /** 37 * A {@link MBFPatchClassificationModel} that performs classification 38 * based on the joint (colour) histogram of the patch by comparing the 39 * patch histogram to a model histogram with a given comparison measure. 40 * 41 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk) 42 */ 43 public class HistogramPatchModel extends MBFPatchClassificationModel { 44 private static final long serialVersionUID = 1L; 45 46 /** 47 * The model histogram; public for speed. 48 */ 49 public HistogramModel model; 50 51 protected DoubleFVComparison compare = DoubleFVComparison.BHATTACHARYYA; 52 53 /** 54 * Construct with the given patch size and number of histogram bins 55 * per dimension. Uses {@link DoubleFVComparison#BHATTACHARYYA} as the 56 * comparison measure. 57 * @param patchWidth patch width. 58 * @param patchHeight patch height. 59 * @param nbins number of bins per dimension. 60 */ 61 public HistogramPatchModel(int patchWidth, int patchHeight, int... nbins) { 62 super(nbins.length, patchWidth, patchHeight); 63 64 model = new HistogramModel(nbins); 65 } 66 67 /** 68 * Construct with the given patch size, comparison measure and ] 69 * number of histogram bins per dimension. 70 * 71 * @param patchWidth patch width. 72 * @param patchHeight patch height. 73 * @param compare comparison measure. 74 * @param nbins number of bins per dimension. 75 */ 76 public HistogramPatchModel(int patchWidth, int patchHeight, DoubleFVComparison compare, int... nbins) { 77 this(patchWidth, patchHeight, nbins); 78 this.compare = compare; 79 model = new HistogramModel(nbins); 80 } 81 82 /** 83 * @return the comparison measure 84 */ 85 public DoubleFVComparison getComparisonMeasure() { 86 return compare; 87 } 88 89 /** 90 * Set the comparison measure used. 91 * @param compare the new comparison measure. 92 */ 93 public void setComparisonMeasure(DoubleFVComparison compare) { 94 this.compare = compare; 95 } 96 97 @Override 98 public float classifyPatch(MBFImage patch) { 99 HistogramModel h = new HistogramModel(model.histogram.nbins); 100 h.estimateModel(patch); 101 return (float) model.histogram.compare(h.histogram, compare); 102 } 103 104 @Override 105 public HistogramPatchModel clone() { 106 HistogramPatchModel newmodel = new HistogramPatchModel(patchWidth, patchHeight, model.histogram.nbins); 107 newmodel.model = model.clone(); 108 109 return newmodel; 110 } 111 112 @Override 113 public void learnModel(MBFImage... images) { 114 model.estimateModel(images); 115 } 116 }