/*
* 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 10:45
*/
package net.semanticmetadata.lire.imageanalysis.features.global;
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.MetricsUtils;
import java.awt.*;
import java.awt.color.ColorSpace;
import java.awt.image.BufferedImage;
import java.awt.image.ColorConvertOp;
/**
* The LuminanceLayout Descriptor is intended for grayscale or B/W images. It scales an image down to a very
* small size and uses this smaller version as a descriptor. Interesting aspect is that white stripes are
* added to make the small image quadratic.
*
* @author Mathias Lux, mathias@juggle.at, 06.04.13
*/
public class LuminanceLayout implements GlobalFeature {
double[] histogram;
int tmp;
static ColorConvertOp grayscale = new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_GRAY),
new RenderingHints(RenderingHints.KEY_INTERPOLATION, RenderingHints.VALUE_INTERPOLATION_BILINEAR));
private int sideLength = 8;
@Override
public void extract(BufferedImage bimg) {
BufferedImage gray = grayscale.filter(bimg, null);
// contrast enhancement didn't go to well with the wang 1000 data set.
// enhanceContrast(gray);
BufferedImage small = new BufferedImage(sideLength, sideLength, BufferedImage.TYPE_BYTE_GRAY);
double scale = (double) Math.max(gray.getWidth(), gray.getHeight()) / 32d;
int w = (int) (gray.getWidth() / scale);
int h = (int) (gray.getHeight() / scale);
int x = 0, y = 0;
if (w < sideLength) x = (sideLength - w) / 2;
if (h < sideLength) y = (sideLength - h) / 2;
small.getGraphics().fillRect(0, 0, sideLength, sideLength);
// small.getGraphics().drawImage(gray, 0, 0, 8, 8, null);
small.getGraphics().drawImage(gray, x, y, w, h, null);
histogram = new double[sideLength * sideLength];
small.getRaster().getPixels(0, 0, sideLength, sideLength, histogram);
for (int i = 0; i < histogram.length; i++) {
histogram[i] = Math.floor(histogram[i] / 8d); // quantize colors to 32 steps ...
}
// histogram = jpgDct(histogram);
}
@SuppressWarnings("unused")
private void enhanceContrast(BufferedImage gray) {
int[] tmp = {0};
double val;
int min = 255, max = 0;
for (int x = 0; x < gray.getWidth(); x++) { // check ...
for (int y = 0; y < gray.getHeight(); y++) {
gray.getRaster().getPixel(x, y, tmp);
min = Math.min(tmp[0], min);
max = Math.max(tmp[0], max);
}
}
if (max < 255 || min > 0) { // enhance ...
double scale = (((double) max) - ((double) min)) / 255d;
for (int x = 0; x < gray.getWidth(); x++) { // check ...
for (int y = 0; y < gray.getHeight(); y++) {
gray.getRaster().getPixel(x, y, tmp);
val = Math.floor(((double) (tmp[0] - min)) / scale);
tmp[0] = (int) val;
gray.getRaster().setPixel(x, y, tmp);
}
}
}
}
@Override
public byte[] getByteArrayRepresentation() {
byte[] result = new byte[histogram.length];
for (int i = 0; i < result.length; i++) {
result[i] = (byte) histogram[i];
// System.out.println("result[i]-histogram[i] = " + (result[i] - histogram[i]));
}
return result;
}
@Override
public void setByteArrayRepresentation(byte[] in) {
histogram = new double[in.length];
for (int i = 0; i < in.length; i++) {
histogram[i] = (double) in[i];
}
}
@Override
public void setByteArrayRepresentation(byte[] in, int offset, int length) {
histogram = new double[length];
for (int i = 0; i < length; i++) {
histogram[i] = (double) in[i+offset];
}
}
@Override
public double[] getFeatureVector() {
return histogram;
}
@Override
public double getDistance(LireFeature feature) {
return MetricsUtils.distL1(histogram, ((LuminanceLayout) feature).histogram);
}
// public String getStringRepresentation() {
// return null;
// }
//
// public void setStringRepresentation(String s) {
// }
// just a 8x8 jpeg dct ...
@SuppressWarnings("unused")
private double[] jpgDct(double[] histogram) {
int[] zickzack = new int[] { 0, 1, 8, 16, 9, 2, 3, 10, 17, 24, 32, 25, 18, 11, 4, 5, 12, 19, 26, 33, 40, 48, 41, 34, 27, 20, 13, 6, 7, 14, 21, 28, 35, 42, 49, 56};
double[] quant = new double[] {16, 5, 6, 7, 6, 5, 8, 7, 7, 7, 9, 8, 8, 9, 12, 20, 13, 12, 11, 11, 12, 25, 18, 18, 15, 20, 28, 25, 30, 30, 28, 25, 28, 27, 32, 36};
// double[] quant = new double[] {16, 11, 12, 14, 12, 10, 16, 14, 13, 14, 18, 17, 16, 19, 24, 40, 26, 24, 22, 22, 24, 49, 35, 37, 29, 40, 58, 51, 61, 60, 57, 51, 56, 55, 64, 72};
double[] coeffs = new double[histogram.length];
int u, v;
double au, av;
for (int i = 0; i < coeffs.length; i++) {
u = i % 8;
v = i / 8;
au = Math.sqrt(2d/6d);
av = Math.sqrt(2d/6d);
if (u==0) au = Math.sqrt(1d/6d);
if (v==0) av = Math.sqrt(1d/6d);
coeffs[i] = 0;
for (int x = 0; x < 8; x++) {
for (int y = 0; y < 8; y++) {
coeffs[i] += au*av*(histogram[i]-127)*Math.cos((Math.PI/8d)*(x+0.5)*u)*Math.cos((Math.PI/8d)*(y+0.5)*v);
}
}
// coeffs[i] = Math.floor(coeffs[i]);
}
double[] result = new double[zickzack.length];
for (int i = 0; i < zickzack.length; i++) {
// result[i] = Math.round(coeffs[zickzack[i]]] / quant[i]);
result[i] = Math.round(coeffs[zickzack[i]] );
}
return result;
}
@SuppressWarnings("unused")
private double[] dct(double[] histogram) {
double[] coeffs = new double[histogram.length / 8];
double N = histogram.length;
double min = 0, max = 0;
for (int i = 0; i < coeffs.length; i++) {
coeffs[i] = 0;
for (int j = 0; j < N; j++) {
coeffs[i] += histogram[j] * Math.cos((Math.PI / N) * (j + 0.5) * (i + 0.5));
}
min = Math.min(min, coeffs[i]);
max = Math.max(max, coeffs[i]);
// result[i] = Math.round(result[i]/1000d);
}
double factor = Math.max(max, Math.abs(min));
for (int i = 0; i < coeffs.length; i++) {
coeffs[i] = Math.floor(coeffs[i] / factor * 63d + 63d);
}
return coeffs;
}
@Override
public String getFeatureName() {
return "Luminance Layout";
}
@Override
public String getFieldName() {
return DocumentBuilder.FIELD_NAME_LUMINANCE_LAYOUT;
}
}