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 }