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.threshold;
031
032import org.openimaj.image.FImage;
033import org.openimaj.image.processing.convolution.FGaussianConvolve;
034import org.openimaj.image.processor.SinglebandImageProcessor;
035
036/**
037 * Adaptive local thresholding using the Gaussian weighted sum of the patch and
038 * an offset.
039 * 
040 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
041 * 
042 */
043public class AdaptiveLocalThresholdGaussian implements SinglebandImageProcessor<Float, FImage> {
044        private float offset;
045        private float sigma;
046
047        /**
048         * Construct the thresholding operator with the given Gaussian standard
049         * deviation, sigma, and offset
050         * 
051         * @param sigma
052         *            Gaussian kernel standard deviation
053         * @param offset
054         *            offset from the patch mean at which the threshold occurs
055         */
056        public AdaptiveLocalThresholdGaussian(float sigma, float offset) {
057                this.sigma = sigma;
058                this.offset = offset;
059        }
060
061        @Override
062        public void processImage(FImage image) {
063                final FImage tmp = image.process(new FGaussianConvolve(sigma));
064
065                final float[][] tpix = tmp.pixels;
066                final float[][] ipix = image.pixels;
067                for (int y = 0; y < image.height; y++)
068                        for (int x = 0; x < image.width; x++)
069                                tpix[y][x] = ipix[y][x] < (tpix[y][x] - offset) ? 0f : 1f;
070
071                image.internalAssign(tmp);
072        }
073}