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.feature.local.detector.dog.extractor; 031 032import gnu.trove.list.array.TFloatArrayList; 033 034import org.openimaj.image.FImage; 035import org.openimaj.image.feature.local.extraction.GradientScaleSpaceImageExtractorProperties; 036 037/** 038 * Extract the dominant orientations of a scale-space interest point by 039 * looking for peaks in its orientation histogram. 040 * 041 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk) 042 */ 043public class DominantOrientationExtractor extends AbstractDominantOrientationExtractor { 044 /** 045 * Default value for the threshold at which other peaks are detected 046 * relative to the biggest peak. Lowe's IJCV paper suggests a 047 * value of 80%. 048 */ 049 public static float DEFAULT_PEAK_THRESHOLD = 0.8f; 050 051 protected OrientationHistogramExtractor oriHistExtractor; 052 053 /** 054 * Threshold for peak detection. A value of 1.0 would 055 * result in only a single peak being detected. 056 */ 057 protected float peakThreshold; 058 059 /** 060 * Construct with default values. 061 */ 062 public DominantOrientationExtractor() { 063 this(DEFAULT_PEAK_THRESHOLD, new OrientationHistogramExtractor()); 064 } 065 066 /** 067 * Construct with given parameters. 068 * @param peakThreshold threshold at which other peaks are detected relative to the biggest peak 069 * @param oriHistExtractor the orientation histogram extractor 070 */ 071 public DominantOrientationExtractor(float peakThreshold, OrientationHistogramExtractor oriHistExtractor) { 072 this.peakThreshold = peakThreshold; 073 this.oriHistExtractor = oriHistExtractor; 074 } 075 076 /** 077 * Extract an orientation histogram and find the dominant orientations 078 * by looking for peaks. 079 * 080 * @param properties Properties describing the interest point in scale space. 081 * @return an array of the angles of the dominant orientations [-PI to PI]. 082 */ 083 @Override 084 public float [] extractFeatureRaw(GradientScaleSpaceImageExtractorProperties<FImage> properties) { 085 //extract histogram 086 float[] hist = getOriHistExtractor().extractFeatureRaw(properties); 087 088 //find max 089 float maxval = 0; 090 for (int i = 0; i < getOriHistExtractor().numBins; i++) 091 if (hist[i] > maxval) 092 maxval = hist[i]; 093 094 float thresh = peakThreshold * maxval; 095 096 //search for peaks within peakThreshold of the maximum 097 TFloatArrayList dominantOrientations = new TFloatArrayList(); 098 for (int i = 0; i < getOriHistExtractor().numBins; i++) { 099 float prevVal = hist[(i == 0 ? getOriHistExtractor().numBins - 1 : i - 1)]; 100 float nextVal = hist[(i == getOriHistExtractor().numBins - 1 ? 0 : i + 1)]; 101 float thisVal = hist[i]; 102 103 if (thisVal >= thresh && thisVal > prevVal && thisVal > nextVal) { 104 //fit a parabola to the peak to find the position of the actual maximum 105 float peakDelta = fitPeak(prevVal, thisVal, nextVal); 106 float angle = 2.0f * (float)Math.PI * (i + 0.5f + peakDelta) / getOriHistExtractor().numBins - (float)Math.PI; 107 108 dominantOrientations.add(angle); 109 } 110 } 111 112 return dominantOrientations.toArray(); 113 } 114 115 /** 116 * Fit a parabola to three evenly spaced samples and return the relative 117 * position of the peak to the second sample. 118 */ 119 float fitPeak(float a, float b, float c) { 120 //a is at x=-1, b at x=0, c at x=1 121 //y = A*x*x + B*x + C 122 //y' = 2*A*x + B 123 //solve for A,B,C then for x where y'=0 124 125 return 0.5f * (a - c) / (a - 2.0f * b + c); 126 } 127 128 129 /** 130 * @return the orientation histogram extractor 131 */ 132 public OrientationHistogramExtractor getOriHistExtractor() { 133 return oriHistExtractor; 134 } 135}