/*
* This file is part of the LIRE project: http://lire-project.net
* LIRE is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* LIRE is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LIRE; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
* We kindly ask you to refer the any or one of the following publications in
* any publication mentioning or employing Lire:
*
* Lux Mathias, Savvas A. Chatzichristofis. Lire: Lucene Image Retrieval –
* An Extensible Java CBIR Library. In proceedings of the 16th ACM International
* Conference on Multimedia, pp. 1085-1088, Vancouver, Canada, 2008
* URL: http://doi.acm.org/10.1145/1459359.1459577
*
* Lux Mathias. Content Based Image Retrieval with LIRE. In proceedings of the
* 19th ACM International Conference on Multimedia, pp. 735-738, Scottsdale,
* Arizona, USA, 2011
* URL: http://dl.acm.org/citation.cfm?id=2072432
*
* Mathias Lux, Oge Marques. Visual Information Retrieval using Java and LIRE
* Morgan & Claypool, 2013
* URL: http://www.morganclaypool.com/doi/abs/10.2200/S00468ED1V01Y201301ICR025
*
* Copyright statement:
* ====================
* (c) 2002-2013 by Mathias Lux (mathias@juggle.at)
* http://www.semanticmetadata.net/lire, http://www.lire-project.net
*
* Updated: 11.07.13 10:36
*/
package net.semanticmetadata.lire.imageanalysis.features.global.joint;
import net.semanticmetadata.lire.builders.DocumentBuilder;
import net.semanticmetadata.lire.imageanalysis.features.GlobalFeature;
import net.semanticmetadata.lire.imageanalysis.features.LireFeature;
import net.semanticmetadata.lire.utils.ImageUtils;
import net.semanticmetadata.lire.utils.MetricsUtils;
import java.awt.image.BufferedImage;
import java.awt.image.WritableRaster;
import java.util.Arrays;
/**
* A simple implementation of the rotation invariant local binary pattern feature.
* @author Mathias Lux, mathias@juggle.at
* Time: 21.06.13 13:51
*/
public class LocalBinaryPatternsAndOpponent implements GlobalFeature {
final static double sq2 = Math.sqrt(2d);
final static double sq6 = Math.sqrt(3d);
final static double sq3 = Math.sqrt(6d);
double[] histogram = new double[36*8];
// used to find the right bin for the class of rotated LBP features.
static int[] binTranslate = new int[256];
static {
Arrays.fill(binTranslate, 0);
binTranslate[0] = 0;
binTranslate[1] = 1;
binTranslate[3] = 2;
binTranslate[5] = 3;
binTranslate[7] = 4;
binTranslate[9] = 5;
binTranslate[11] = 6;
binTranslate[13] = 7;
binTranslate[15] = 8;
binTranslate[17] = 9;
binTranslate[19] = 10;
binTranslate[21] = 11;
binTranslate[23] = 12;
binTranslate[25] = 13;
binTranslate[27] = 14;
binTranslate[29] = 15;
binTranslate[31] = 16;
binTranslate[37] = 17;
binTranslate[39] = 18;
binTranslate[43] = 19;
binTranslate[45] = 20;
binTranslate[47] = 21;
binTranslate[51] = 22;
binTranslate[53] = 23;
binTranslate[55] = 24;
binTranslate[59] = 25;
binTranslate[61] = 26;
binTranslate[63] = 27;
binTranslate[85] = 28;
binTranslate[87] = 29;
binTranslate[91] = 30;
binTranslate[95] = 31;
binTranslate[111] = 32;
binTranslate[119] = 33;
binTranslate[127] = 34;
binTranslate[255] = 35;
}
@Override
public void extract(BufferedImage image) {
Arrays.fill(histogram, 0d);
extractWithRadiusOne(image);
}
/**
* Extracts the classical, radius = 1 version.
* @param image
*/
private void extractWithRadiusOne(BufferedImage image) {
double o1,o2,o3;
int colorPos = 0;
// first convert to intensity only.
WritableRaster raster = ImageUtils.getGrayscaleImage(image).getRaster();
WritableRaster rasterColor = image.getRaster();
// cached pixel array
int[] pixel = new int[9];
int[] pattern = new int[8];
int[] px = new int[3];
// now fill histogram according to LBP definition.
for (int x = 0; x < raster.getWidth() - 2; x++) {
for (int y = 0; y < raster.getHeight() - 2; y++) {
Arrays.fill(pattern, 0);
raster.getPixels(x, y, 3, 3, pixel);
if (pixel[0] >= pixel[4]) pattern[0] = 1;
if (pixel[1] >= pixel[4]) pattern[1] = 1;
if (pixel[2] >= pixel[4]) pattern[2] = 1;
if (pixel[5] >= pixel[4]) pattern[3] = 1;
if (pixel[8] >= pixel[4]) pattern[4] = 1;
if (pixel[7] >= pixel[4]) pattern[5] = 1;
if (pixel[6] >= pixel[4]) pattern[6] = 1;
if (pixel[3] >= pixel[4]) pattern[7] = 1;
rasterColor.getPixel(x,y,px);
o1 = (double) (px[0] - px[1]) / sq2;
o2 = (double) (px[0] + px[1] - 2 * px[2]) / sq6;
o3 = (double) (px[0] + px[1] + px[2]) / sq3;
// Normalize ... easier to handle.
o1 = (o1 + 255d / sq2) / (510d / sq2);
o2 = (o2 + 510d / sq6) / (1020d / sq6);
o3 = o3 / (3d * 255d / sq3);
// get the array position.
colorPos = (int) Math.min(Math.floor(o1 * 2d), 1d) + (int) Math.min(Math.floor(o2 * 2d), 1d) * 2 + (int) Math.min(Math.floor(o3 * 2d), 1d) * 2* 2;
histogram[colorPos*36+getBin(pattern)]++;
}
}
// normalize & quantize histogram.
double max = 0;
for (int i = 0; i < histogram.length; i++) {
max = Math.max(histogram[i], max);
}
for (int i = 0; i < histogram.length; i++) {
histogram[i] = Math.floor((histogram[i] / max) * 8);
}
}
private int getBin(int[] pattern) {
// add the rotation invariant code here ...
int min = Integer.MAX_VALUE;
for (int i = 0; i < 8; i++) {
min = Math.min(getNumber(pattern), min);
// rotate:
int tmp = pattern[7];
for (int j = pattern.length-1; j > 0; j--) {
pattern[j] = pattern[j-1];
}
pattern[0] = tmp;
}
return binTranslate[min];
}
private int getNumber(int[] pattern) {
int result = 0;
int current = 1;
for (int i = 0; i < pattern.length; i++) {
if (pattern[i]>0) result+=current;
current*=2;
}
return result;
}
@Override
public byte[] getByteArrayRepresentation() {
byte[] rep = new byte[histogram.length];
for (int i = 0; i < histogram.length; i++) {
rep[i] = (byte) histogram[i];
}
return rep;
}
@Override
public void setByteArrayRepresentation(byte[] in) {
setByteArrayRepresentation(in, 0, in.length);
}
@Override
public void setByteArrayRepresentation(byte[] in, int offset, int length) {
for (int i = offset; i < offset + length; i++) {
histogram[i - offset] = in[i];
}
}
@Override
public double[] getFeatureVector() {
return histogram;
}
@Override
public double getDistance(LireFeature feature) {
return MetricsUtils.tanimoto(histogram, feature.getFeatureVector());
}
// @Override
// public String getStringRepresentation() {
// throw new UnsupportedOperationException("Not implemented!");
// }
//
// @Override
// public void setStringRepresentation(String s) {
// throw new UnsupportedOperationException("Not implemented!");
// }
@Override
public String getFeatureName() {
return "LBP Opponent Joint Histogram";
}
@Override
public String getFieldName() {
return DocumentBuilder.FIELD_NAME_LOCAL_BINARY_PATTERNS_AND_OPPONENT;
}
}