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.convolution;
031
032import org.openimaj.image.FImage;
033import org.openimaj.image.analyser.ImageAnalyser;
034
035/**
036 * Helper {@link ImageAnalyser} that computes the X and Y image gradients using
037 * Sobel filters. Optionally, the input image can be blurred first using a
038 * Gaussian.
039 * 
040 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
041 */
042public class FSobel implements ImageAnalyser<FImage> {
043        private float sigma;
044
045        /**
046         * The X gradients
047         */
048        public FImage dx;
049
050        /**
051         * The Y gradients
052         */
053        public FImage dy;
054
055        /**
056         * Construct with no Gaussian blurring
057         */
058        public FSobel() {
059                this(0);
060        }
061
062        /**
063         * Construct with an initial Gaussian blurring of the given standard
064         * deviation.
065         * 
066         * @param sigma
067         *            the standard deviation of the Gaussian blur
068         */
069        public FSobel(float sigma) {
070                this.sigma = sigma;
071        }
072
073        @Override
074        public void analyseImage(FImage image) {
075                final FImage tmp = sigma == 0 ? image : image.process(new FGaussianConvolve(sigma));
076                dx = tmp.process(new FSobelX());
077                dy = tmp.process(new FSobelY());
078        }
079}