/**
 * 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
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 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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package org.openimaj.image.feature.dense.binarypattern;

import org.openimaj.citation.annotation.Reference;
import org.openimaj.citation.annotation.ReferenceType;
import org.openimaj.image.FImage;
import org.openimaj.image.analyser.ImageAnalyser;
import org.openimaj.image.pixel.Pixel;

/**
 * Implementation of a Local Ternary Pattern.
 * 
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 */
@Reference(
                type = ReferenceType.Article,
                author = { "Tan, Xiaoyang", "Triggs, Bill" },
                title = "Enhanced local texture feature sets for face recognition under difficult lighting conditions",
                year = "2010",
                journal = "Trans. Img. Proc.",
                pages = { "1635", "", "1650" },
                url = "http://dx.doi.org/10.1109/TIP.2010.2042645",
                month = "June",
                number = "6",
                publisher = "IEEE Press",
                volume = "19"
        )
public class LocalTernaryPattern implements ImageAnalyser<FImage> {
        protected int[][] positiveBinaryPattern;
        protected int[][] negativeBinaryPattern;
        protected int[][] ternaryPattern;
        
        protected float radius;
        protected int samples;
        protected float threshold;
        
        /**
         * Construct an LTP extractor with the given parameters.
         * @param radius the radius of the sampling circle
         * @param samples the number of samples around the circle
         * @param threshold the threshold
         */
        public LocalTernaryPattern(float radius, int samples, float threshold) {
                checkParams(radius, samples);
                this.radius = radius;
                this.samples = samples;
                this.threshold = threshold;
        }
        
        /**
         * Calculate the LBP for every pixel in the image. The returned
         * array of LBP codes hase the same dimensions as the image. 
         * 
         * Samples taken from outside the image bounds are assumed to have 
         * the value 0.
         * 
         * @param image the image
         * @param radius the radius of the sampling circle
         * @param samples the number of samples around the circle
         * @param threshold the threshold
         * @return three 2d-arrays of the positive and negative binary LTP codes and the ternary code for every pixel
         */
        public static int[][][] calculateLTP(FImage image, float radius, int samples, float threshold) {
                checkParams(radius, samples);
                
                int [][][] pattern = new int[3][image.height][image.width];
                
                for (int y=0; y<image.height; y++) {
                        for (int x=0; x<image.width; x++) {
                                int [] pn = calculateLTP(image, radius, samples, threshold, x, y);
                                pattern[0][y][x] = pn[0];
                                pattern[1][y][x] = pn[1];
                                pattern[2][y][x] = pn[2];
                        }
                }
                
                return pattern;
        }
        
        /**
         * Calculate the LTP for a single point. The
         * point must be within the image.
         * 
         * @param image the image
         * @param radius the radius of the sampling circle
         * @param samples the number of samples around the circle
         * @param threshold the threshold
         * @param x the x-coordinate of the point
         * @param y the y-coordinate of the point
         * @return the LTP code (positive and negative binary code and ternary code)
         */
        public static int[] calculateLTP(FImage image, float radius, int samples, float threshold, int x, int y) {
                float centre = image.pixels[y][x];
                int pattern[] = new int[3];
                
                for (int i=0; i<samples; i++) {
                        double xx = -radius * Math.sin(2 * Math.PI * i / samples);
                        double yy = radius * Math.cos(2 * Math.PI * i / samples);
                        
                        float pix = image.getPixelInterp(x+xx, y+yy);
                        
                        float d = pix - centre;
                        
                        if (d >= threshold) {
                                pattern[0] += Math.pow(2, i);
                                pattern[2] += Math.pow(3, i);
                        }
                        if (d <= threshold) {
                                pattern[1] += Math.pow(2, i);
                                pattern[2] += 2 * Math.pow(3, i);
                        }
                }
                
                return pattern;
        }

        /**
         * Calculate the LTP for a single point. The
         * point must be within the image.
         * 
         * @param image the image
         * @param radius the radius of the sampling circle
         * @param threshold the threshold
         * @param samples the number of samples around the circle
         * @param point the point
         * @return the LTP code (positive and negative binary code and ternary code)
         */
        public static int [] calculateLTP(FImage image, float radius, int samples, float threshold, Pixel point) {
                return calculateLTP(image, radius, samples, threshold, point.x, point.y);
        }

        private static void checkParams(float radius, int samples) {
                if (radius <= 0) {
                        throw new IllegalArgumentException("radius must be greater than 0");
                }
                if (samples <= 1 || samples > 31) {
                        throw new IllegalArgumentException("samples cannot be less than one or more than 31");
                }
        }

        /* (non-Javadoc)
         * @see org.openimaj.image.analyser.ImageAnalyser#analyseImage(org.openimaj.image.Image)
         */
        @Override
        public void analyseImage(FImage image) {
                int [][][] patterns = calculateLTP(image, radius, samples, threshold);
                
                positiveBinaryPattern = patterns[0];
                negativeBinaryPattern = patterns[1];
                ternaryPattern = patterns[2];
        }
        
        /**
         * Get the positive pattern created during the last call to
         * {@link #analyseImage(FImage)}.
         * 
         * @return the pattern
         */
        public int[][] getPositivePattern() {
                return positiveBinaryPattern;
        }
        
        /**
         * Get the negative pattern created during the last call to
         * {@link #analyseImage(FImage)}.
         * 
         * @return the pattern
         */
        public int[][] getNegativePattern() {
                return negativeBinaryPattern;
        }
        
        /**
         * Get the ternary pattern created during the last call to
         * {@link #analyseImage(FImage)}.
         * 
         * @return the pattern
         */
        public int[][] getTernaryPattern() {
                return ternaryPattern;
        }
}