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.processing.face.feature.ltp;
031
032import java.io.DataInput;
033import java.io.DataOutput;
034import java.io.IOException;
035
036import org.openimaj.citation.annotation.Reference;
037import org.openimaj.citation.annotation.ReferenceType;
038
039/**
040 * A Gaussian {@link LTPWeighting} function. 
041 * 
042 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
043 */
044@Reference(
045                type = ReferenceType.Article,
046                author = { "Tan, Xiaoyang", "Triggs, Bill" },
047                title = "Enhanced local texture feature sets for face recognition under difficult lighting conditions",
048                year = "2010",
049                journal = "Trans. Img. Proc.",
050                pages = { "1635", "1650" },
051                url = "http://dx.doi.org/10.1109/TIP.2010.2042645",
052                month = "June",
053                number = "6",
054                publisher = "IEEE Press",
055                volume = "19"
056        )
057public class GaussianWeighting implements LTPWeighting {
058        private float sigma = 3;
059        
060        /**
061         * Construct with a default standard deviation of 3.0
062         */
063        public GaussianWeighting() {}
064        
065        /**
066         * Construct with the given standard deviation
067         * @param sigma the standard deviation
068         */
069        public GaussianWeighting(float sigma) {
070                this.sigma= sigma;
071        }
072        
073        @Override
074        public float weightDistance(float distance) {
075                return (float) Math.exp( -(distance * distance) / (sigma * sigma * 2));
076        }
077
078        @Override
079        public void readBinary(DataInput in) throws IOException {
080                sigma = in.readFloat();
081        }
082
083        @Override
084        public byte[] binaryHeader() {
085                return this.getClass().getName().getBytes();
086        }
087
088        @Override
089        public void writeBinary(DataOutput out) throws IOException {
090                out.writeFloat(sigma);
091        }
092        
093        @Override
094        public String toString() {
095                return "GaussianWeighting[sigma="+sigma+"]";
096        }
097}