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Methods for the extraction of local features. Local features are descriptions of regions of images (SIFT, ...) selected by detectors (Difference of Gaussian, Harris, ...).

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/**
 * Copyright (c) 2011, The University of Southampton and the individual contributors.
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification,
 * are permitted provided that the following conditions are met:
 *
 *   * 	Redistributions of source code must retain the above copyright notice,
 * 	this list of conditions and the following disclaimer.
 *
 *   *	Redistributions in binary form must reproduce the above copyright notice,
 * 	this list of conditions and the following disclaimer in the documentation
 * 	and/or other materials provided with the distribution.
 *
 *   *	Neither the name of the University of Southampton nor the names of its
 * 	contributors may be used to endorse or promote products derived from this
 * 	software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
package org.openimaj.feature.local.matcher;

import java.util.ArrayList;
import java.util.List;
import java.util.PriorityQueue;
import java.util.Queue;

import org.openimaj.image.feature.local.keypoints.Keypoint;
import org.openimaj.knn.approximate.ByteNearestNeighboursKDTree;
import org.openimaj.util.pair.Pair;


/**
 * Basic keypoint matcher. Matches keypoints by finding closest
 * Two keypoints to target and checking whether the distance
 * between the two matches is sufficiently large. Allows for a match limit to be specified
 * 
 * @author Jonathon Hare ([email protected])
 * @author Sina Samangooei ([email protected])
 *
 * @param 
 */
public class FastLimitedEuclideanKeypointMatcher implements LocalFeatureMatcher {
	private ByteNearestNeighboursKDTree modelKeypointsKNN;
	private int limit;
	private List> matches;
	private List modelKeypoints;
	
	/**
	 * Number of matches allowed
	 * @param limit
	 */
	public FastLimitedEuclideanKeypointMatcher(int limit) {
		this.limit = limit;
	}

	@Override
	public void setModelFeatures(List modelkeys) {
		modelKeypoints = modelkeys;
		
		byte [][] data = new byte[modelkeys.size()][];
		for (int i=0; i implements Comparable {
		float weight;

		public WPair(T obj1, T obj2, float weight) {
			super(obj1, obj2);
			this.weight = weight;
		}

		@Override
		public int compareTo(WPair o) {
			if (weight == o.weight) return 0;
			if (weight < o.weight) return -1;
			return 1;
		}
	}
	
	@Override
	public boolean findMatches(List keys1) {
		Queue mq = new PriorityQueue();
		
		byte [][] data = new byte[keys1.size()][];
		for (int i=0; i>(limit);
		for (int i=0; i> getMatches() {
		return matches;
	}

}