/**
 * 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;
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package org.openimaj.image.feature.dense.binarypattern;

import gnu.trove.list.array.TIntArrayList;

import org.openimaj.citation.annotation.Reference;
import org.openimaj.citation.annotation.ReferenceType;
import org.openimaj.feature.FloatFV;

/**
 * Class for extracting histograms of Local Uniform Binary Patterns. Uniform
 * patterns have less than one 01 transition and one 01 transition when viewed
 * as a circular buffer.
 * 
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 */
@Reference(
                type = ReferenceType.Article,
                author = { "Ojala, T.", "Pietikainen, M.", "Maenpaa, T." },
                title = "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns",
                year = "2002",
                journal = "Pattern Analysis and Machine Intelligence, IEEE Transactions on",
                pages = { "971 ", "987" },
                month = "jul",
                number = "7",
                volume = "24",
                customData = {
                                "doi", "10.1109/TPAMI.2002.1017623",
                                "ISSN", "0162-8828"
                })
public class LocalUniformBinaryPatternHistogram {
        protected int blocksize_x;
        protected int blocksize_y;
        FloatFV[][] histograms;

        /**
         * Construct the extractor with the given block size for each local patch.
         * 
         * @param blocksize_x
         *            the width of the blocks
         * @param blocksize_y
         *            the height of the blocks
         */
        public LocalUniformBinaryPatternHistogram(int blocksize_x, int blocksize_y) {
                this.blocksize_x = blocksize_x;
                this.blocksize_y = blocksize_y;
        }

        /**
         * Compute the histograms for the given pattern image, encoded with the
         * given number of bits.
         * 
         * @param patternImage
         *            the pattern data
         * @param nbits
         *            the number of bits used to encode the patterns
         */
        public void calculateHistograms(int[][] patternImage, int nbits) {
                final int height = patternImage.length;
                final int width = patternImage[0].length;
                final TIntArrayList uniformPatterns = UniformBinaryPattern.getUniformPatterns(nbits);

                histograms = new FloatFV[(int) Math.ceil((double) height / (double) blocksize_y)][(int) Math.ceil((double) width
                                / (double) blocksize_x)];

                for (int y = 0, j = 0; y < height; y += blocksize_y, j++) {
                        for (int x = 0, i = 0; x < width; x += blocksize_x, i++) {
                                histograms[j][i] = new FloatFV(uniformPatterns.size() + 1);

                                for (int yy = y; yy < Math.min(height, y + blocksize_y); yy++) {
                                        for (int xx = x; xx < Math.min(width, x + blocksize_x); xx++) {
                                                final int idx = uniformPatterns.indexOf(patternImage[yy][xx]);

                                                histograms[j][i].values[idx + 1]++;
                                        }
                                }
                        }
                }
        }

        /**
         * Get the histograms
         * 
         * @return the histograms
         */
        public FloatFV[][] getHistograms() {
                return histograms;
        }

        /**
         * Get the histograms as a single {@link FloatFV}.
         * 
         * @return the histograms
         */
        public FloatFV getHistogram() {
                final int len = histograms[0][0].length();
                final FloatFV h = new FloatFV(histograms.length * histograms[0].length * len);

                for (int j = 0; j < histograms.length; j++) {
                        for (int i = 0; i < histograms[0].length; i++) {
                                final int blkid = i + j * histograms[0].length;
                                System.arraycopy(histograms[j][i].values, 0, h.values, blkid * len, len);
                        }
                }

                return h;
        }
}