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.collector; 031 032 033import org.openimaj.feature.OrientedFeatureVector; 034import org.openimaj.image.FImage; 035import org.openimaj.image.Image; 036import org.openimaj.image.analysis.pyramid.gaussian.GaussianOctave; 037import org.openimaj.image.feature.local.detector.dog.extractor.ScaleSpaceFeatureExtractor; 038import org.openimaj.image.feature.local.detector.pyramid.OctaveInterestPointFinder; 039import org.openimaj.image.feature.local.extraction.ScaleSpaceImageExtractorProperties; 040import org.openimaj.image.feature.local.keypoints.Keypoint; 041import org.openimaj.image.processor.SinglebandImageProcessor; 042 043/** 044 * Concrete implementation of an {@link AbstractOctaveLocalFeatureCollector} 045 * that collects {@link Keypoint}s with the feature vector provided by the 046 * given feature extractor. {@link Keypoint}s contain the x, y and scale 047 * coordinates of the interest point along with its dominant orientation 048 * 049 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk) 050 * 051 * @param <IMAGE> Type of underlying {@link Image} 052 */ 053public class OctaveKeypointCollector< 054 IMAGE extends Image<?,IMAGE> & SinglebandImageProcessor.Processable<Float,FImage,IMAGE>> 055 extends 056 AbstractOctaveLocalFeatureCollector< 057 GaussianOctave<IMAGE>, 058 ScaleSpaceFeatureExtractor<OrientedFeatureVector, IMAGE>, 059 Keypoint, 060 IMAGE 061 > 062{ 063 protected ScaleSpaceImageExtractorProperties<IMAGE> extractionProperties = new ScaleSpaceImageExtractorProperties<IMAGE>(); 064 065 /** 066 * Construct with the given feature extractor. 067 * @param featureExtractor the feature extractor. 068 */ 069 public OctaveKeypointCollector(ScaleSpaceFeatureExtractor<OrientedFeatureVector, IMAGE> featureExtractor) { 070 super(featureExtractor); 071 } 072 073 @Override 074 public void foundInterestPoint(OctaveInterestPointFinder<GaussianOctave<IMAGE>, IMAGE> finder, float x, float y, float octaveScale) { 075 int currentScaleIndex = finder.getCurrentScaleIndex(); 076 extractionProperties.image = finder.getOctave().images[currentScaleIndex]; 077 extractionProperties.scale = octaveScale; 078 extractionProperties.x = x; 079 extractionProperties.y = y; 080 081 float octSize = finder.getOctave().octaveSize; 082 083 addFeature(octSize * x, octSize * y, octSize * octaveScale); 084 } 085 086 protected void addFeature(float imx, float imy, float imscale) { 087 OrientedFeatureVector[] fvs = featureExtractor.extractFeature(extractionProperties); 088 089 for (OrientedFeatureVector fv : fvs) { 090 features.add(new Keypoint(imx, imy, fv.orientation, imscale, fv.values)); 091 } 092 } 093}