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.image.model.patch; 031 032import org.openimaj.feature.DoubleFVComparison; 033import org.openimaj.image.MBFImage; 034import org.openimaj.image.pixel.statistics.HistogramModel; 035 036/** 037 * A {@link MBFPatchClassificationModel} that performs classification 038 * based on the joint (colour) histogram of the patch by comparing the 039 * patch histogram to a model histogram with a given comparison measure. 040 * 041 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk) 042 */ 043public class HistogramPatchModel extends MBFPatchClassificationModel { 044 private static final long serialVersionUID = 1L; 045 046 /** 047 * The model histogram; public for speed. 048 */ 049 public HistogramModel model; 050 051 protected DoubleFVComparison compare = DoubleFVComparison.BHATTACHARYYA; 052 053 /** 054 * Construct with the given patch size and number of histogram bins 055 * per dimension. Uses {@link DoubleFVComparison#BHATTACHARYYA} as the 056 * comparison measure. 057 * @param patchWidth patch width. 058 * @param patchHeight patch height. 059 * @param nbins number of bins per dimension. 060 */ 061 public HistogramPatchModel(int patchWidth, int patchHeight, int... nbins) { 062 super(nbins.length, patchWidth, patchHeight); 063 064 model = new HistogramModel(nbins); 065 } 066 067 /** 068 * Construct with the given patch size, comparison measure and ] 069 * number of histogram bins per dimension. 070 * 071 * @param patchWidth patch width. 072 * @param patchHeight patch height. 073 * @param compare comparison measure. 074 * @param nbins number of bins per dimension. 075 */ 076 public HistogramPatchModel(int patchWidth, int patchHeight, DoubleFVComparison compare, int... nbins) { 077 this(patchWidth, patchHeight, nbins); 078 this.compare = compare; 079 model = new HistogramModel(nbins); 080 } 081 082 /** 083 * @return the comparison measure 084 */ 085 public DoubleFVComparison getComparisonMeasure() { 086 return compare; 087 } 088 089 /** 090 * Set the comparison measure used. 091 * @param compare the new comparison measure. 092 */ 093 public void setComparisonMeasure(DoubleFVComparison compare) { 094 this.compare = compare; 095 } 096 097 @Override 098 public float classifyPatch(MBFImage patch) { 099 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}