/*
* 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 10:41
*/
package net.semanticmetadata.lire.imageanalysis.features.global.spatialpyramid;
import net.semanticmetadata.lire.imageanalysis.features.GlobalFeature;
import net.semanticmetadata.lire.imageanalysis.features.LireFeature;
import net.semanticmetadata.lire.imageanalysis.features.global.AutoColorCorrelogram;
import net.semanticmetadata.lire.utils.MetricsUtils;
import java.awt.image.BufferedImage;
/**
* Created with IntelliJ IDEA.
* User: mlux
* Date: 28.05.13
* Time: 16:11
* To change this template use File | Settings | File Templates.
*/
public class SPACC implements GlobalFeature {
// private int histLength = 1024;
private int histLength = 256;
// int histogramSize = histLength * 4 * 4;
int histogramSize = histLength * 5 + histLength * 4 * 4;
double[] histogram = new double[histogramSize];
// Temp:
int tmp;
@Override
public void extract(BufferedImage bimg) {
// level 0:
AutoColorCorrelogram acc = new AutoColorCorrelogram();
acc.extract(bimg);
System.arraycopy(acc.getFeatureVector(), 0, histogram, 0, histLength);
// level 1:
int w = bimg.getWidth() / 2;
int h = bimg.getHeight() / 2;
acc.extract(bimg.getSubimage(0, 0, w, h));
System.arraycopy(acc.getFeatureVector(), 0, histogram, histLength * 1, histLength);
acc.extract(bimg.getSubimage(w, 0, w, h));
System.arraycopy(acc.getFeatureVector(), 0, histogram, histLength * 2, histLength);
acc.extract(bimg.getSubimage(0, h, w, h));
System.arraycopy(acc.getFeatureVector(), 0, histogram, histLength * 3, histLength);
acc.extract(bimg.getSubimage(w, h, w, h));
System.arraycopy(acc.getFeatureVector(), 0, histogram, histLength * 4, histLength);
// level 2:
int wstep = bimg.getWidth() / 4;
int hstep = bimg.getHeight() / 4;
int binPos = 5; // the next free section in the histogram
for (int i = 0; i < 4; i++) {
for (int j = 0; j < 4; j++) {
acc.extract(bimg.getSubimage(i * wstep, j * hstep, wstep, hstep));
System.arraycopy(acc.getFeatureVector(), 0, histogram, histLength * binPos, histLength);
binPos++;
}
}
}
/**
* Provides a faster way of serialization.
*
* @return a byte array that can be read with the corresponding method.
* @see SPJCD#setByteArrayRepresentation(byte[])
*/
public byte[] getByteArrayRepresentation() {
byte[] result = new byte[histogramSize/2];
for (int i = 0; i < result.length; i++) {
tmp = ((int) (histogram[(i << 1)])) << 4;
tmp = (tmp | ((int) (histogram[(i << 1) + 1])));
result[i] = (byte) (tmp - 128);
}
return result;
}
/**
* Reads descriptor from a byte array. Much faster than the String based method.
*
* @param in byte array from corresponding method
* @see SPJCD#getByteArrayRepresentation
*/
public void setByteArrayRepresentation(byte[] in) {
setByteArrayRepresentation(in, 0, in.length);
}
public void setByteArrayRepresentation(byte[] in, int offset, int length) {
for (int i = offset; i < offset + length; i++) {
tmp = in[i] + 128;
histogram[((i - offset) << 1) + 1] = ((double) (tmp & 0x000F));
histogram[(i - offset) << 1] = ((double) (tmp >> 4));
}
}
@Override
public double[] getFeatureVector() {
return histogram;
}
@Override
public double getDistance(LireFeature feature) {
if (!(feature instanceof SPACC)) return -1;
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 "Auto Color Correlogram Spatial Pyramid";
}
@Override
public String getFieldName() {
return "f_spacc";
}
}