/*
* 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;
/**
* A simple implementation of a joint opponent histogram combining 64-bin RGB and pixel rank.
*
* @author Mathias Lux, mathias@juggle.at
*/
public class RankAndOpponent implements GlobalFeature {
private int[] tmpIntensity = new int[1];
final double sq2 = Math.sqrt(2d);
final double sq6 = Math.sqrt(3d);
final double sq3 = Math.sqrt(6d);
double[] descriptor;
double o1, o2, o3;
int tmp;
public RankAndOpponent() {
descriptor = new double[64 * 9];
}
@Override
public void extract(BufferedImage bimg) {
// extract:
int[][] histogram = new int[64][9];
for (int i = 0; i < histogram.length; i++) {
for (int j = 0; j < histogram[i].length; j++)
histogram[i][j] = 0;
}
WritableRaster grey = ImageUtils.getGrayscaleImage(bimg).getRaster();
WritableRaster raster = bimg.getRaster();
int[] px = new int[3];
int[] intens = new int[1];
int colorPos;
for (int x = 1; x < raster.getWidth() - 1; x++) {
for (int y = 1; y < raster.getHeight() - 1; y++) {
raster.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 * 4d), 3d) + (int) Math.min(Math.floor(o2 * 4d), 3d) * 4 + (int) Math.min(3d, Math.floor(o3 * 4d)) * 4 * 4;
int rank = 0;
grey.getPixel(x, y, intens);
if (getIntensity(x - 1, y - 1, grey) > intens[0]) rank++;
if (getIntensity(x, y - 1, grey) > intens[0]) rank++;
if (getIntensity(x + 1, y - 1, grey) > intens[0]) rank++;
if (getIntensity(x - 1, y + 1, grey) > intens[0]) rank++;
if (getIntensity(x, y + 1, grey) > intens[0]) rank++;
if (getIntensity(x + 1, y + 1, grey) > intens[0]) rank++;
if (getIntensity(x - 1, y, grey) > intens[0]) rank++;
if (getIntensity(x + 1, y, grey) > intens[0]) rank++;
histogram[colorPos][rank]++;
}
}
// normalize with max norm & quantize to [0,7]:
descriptor = new double[64 * 9];
double max = 0;
for (int i = 0; i < histogram.length; i++) {
for (int j = 0; j < histogram[i].length; j++) {
max = Math.max(histogram[i][j], max);
}
}
for (int i = 0; i < histogram.length; i++) {
for (int j = 0; j < histogram[i].length; j++) {
descriptor[i + 64 * j] = Math.floor(7d * (histogram[i][j] / max));
}
}
}
private int getIntensity(int x, int y, WritableRaster grey) {
grey.getPixel(x, y, tmpIntensity);
return tmpIntensity[0];
}
// public String getStringRepresentation() {
// StringBuilder sb = new StringBuilder(descriptor.length * 2 + 25);
// sb.append("jophist");
// sb.append(' ');
// sb.append(descriptor.length);
// sb.append(' ');
// for (double aData : descriptor) {
// sb.append((int) aData);
// sb.append(' ');
// }
// return sb.toString().trim();
// }
//
// public void setStringRepresentation(String s) {
// StringTokenizer st = new StringTokenizer(s);
// if (!st.nextToken().equals("jophist"))
// throw new UnsupportedOperationException("This is not a RankAndOpponent descriptor.");
// descriptor = new double[Integer.parseInt(st.nextToken())];
// for (int i = 0; i < descriptor.length; i++) {
// if (!st.hasMoreTokens())
// throw new IndexOutOfBoundsException("Too few numbers in string representation.");
// descriptor[i] = Integer.parseInt(st.nextToken());
// }
//
// }
@Override
public byte[] getByteArrayRepresentation() {
byte[] result = new byte[descriptor.length/2];
for (int i = 0; i < result.length; i++) {
tmp = ((int) (descriptor[(i << 1)] * 2)) << 4;
tmp = (tmp | ((int) (descriptor[(i << 1) + 1] * 2)));
result[i] = (byte) (tmp-128);
}
return result;
}
@Override
public void setByteArrayRepresentation(byte[] in) {
for (int i = 0; i < in.length; i++) {
tmp = in[i]+128;
descriptor[(i << 1) +1] = ((double) (tmp & 0x000F))/2d;
descriptor[i << 1] = ((double) (tmp >> 4))/2d;
}
}
@Override
public void setByteArrayRepresentation(byte[] in, int offset, int length) {
for (int i = offset; i < length; i++) {
tmp = in[i]+128;
descriptor[(i << 1) +1] = ((double) (tmp & 0x000F))/2d;
descriptor[i << 1] = ((double) (tmp >> 4))/2d;
}
}
@Override
public double[] getFeatureVector() {
double[] result = new double[descriptor.length];
for (int i = 0; i < descriptor.length; i++) {
result[i] = descriptor[i];
}
return result;
}
@Override
public double getDistance(LireFeature feature) {
if (!(feature instanceof RankAndOpponent))
throw new UnsupportedOperationException("Wrong descriptor.");
return MetricsUtils.jsd(((RankAndOpponent) feature).descriptor, descriptor);
}
@Override
public String getFeatureName() {
return "Rank Opponent Joint Histogram";
}
@Override
public String getFieldName() {
return DocumentBuilder.FIELD_NAME_Rank_Opponent;
}
}