LIRe 源代码分析 5:提取特征向量[以颜色布局为例]
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LIRe源代码分析系列文章列表:
LIRe 源代码分析 2:基本接口(DocumentBuilder)
LIRe 源代码分析 3:基本接口(ImageSearcher)
LIRe 源代码分析 4:建立索引(DocumentBuilder)[以颜色布局为例]
LIRe 源代码分析 6:检索(ImageSearcher)[以颜色布局为例]
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在上一篇文章中,讲述了建立索引的过程。这里继续上一篇文章的分析。在ColorLayoutDocumentBuilder中,使用了一个类型为ColorLayout的对象vd,并且调用了vd的extract()方法:
ColorLayout vd = new ColorLayout(); vd.extract(bimg);
此外调用了vd的getByteArrayRepresentation()方法:
new Field(DocumentBuilder.FIELD_NAME_COLORLAYOUT_FAST, vd.getByteArrayRepresentation())
在这里我们看一看ColorLayout是个什么类。ColorLayout位于“net.semanticmetadata.lire.imageanalysis”包中,如下图所示:
由图可见,这个包中有很多的类。这些类都是以检索方法的名字命名的。我们要找的ColorLayout类也在其中。看看它的代码吧:
/* * This file is part of the LIRe project: http://www.semanticmetadata.net/lire * 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 following paper in any publication mentioning Lire: * * Lux Mathias, Savvas A. Chatzichristofis. Lire: Lucene Image Retrieval 鈥� * An Extensible Java CBIR Library. In proceedings of the 16th ACM International * Conference on Multimedia, pp. 1085-1088, Vancouver, Canada, 2008 * * http://doi.acm.org/10.1145/1459359.1459577 * * Copyright statement: * -------------------- * (c) 2002-2011 by Mathias Lux (mathias@juggle.at) * http://www.semanticmetadata.net/lire */ package net.semanticmetadata.lire.imageanalysis; import net.semanticmetadata.lire.imageanalysis.mpeg7.ColorLayoutImpl; import net.semanticmetadata.lire.utils.SerializationUtils; /** * Just a wrapper for the use of LireFeature. * Date: 27.08.2008 * Time: 12:07:38 * * @author Mathias Lux, mathias@juggle.at */ public class ColorLayout extends ColorLayoutImpl implements LireFeature { /* public String getStringRepresentation() { StringBuilder sb = new StringBuilder(256); StringBuilder sbtmp = new StringBuilder(256); for (int i = 0; i < numYCoeff; i++) { sb.append(YCoeff[i]); if (i + 1 < numYCoeff) sb.append(' '); } sb.append("z"); for (int i = 0; i < numCCoeff; i++) { sb.append(CbCoeff[i]); if (i + 1 < numCCoeff) sb.append(' '); sbtmp.append(CrCoeff[i]); if (i + 1 < numCCoeff) sbtmp.append(' '); } sb.append("z"); sb.append(sbtmp); return sb.toString(); } public void setStringRepresentation(String descriptor) { String[] coeffs = descriptor.split("z"); String[] y = coeffs[0].split(" "); String[] cb = coeffs[1].split(" "); String[] cr = coeffs[2].split(" "); numYCoeff = y.length; numCCoeff = Math.min(cb.length, cr.length); YCoeff = new int[numYCoeff]; CbCoeff = new int[numCCoeff]; CrCoeff = new int[numCCoeff]; for (int i = 0; i < numYCoeff; i++) { YCoeff[i] = Integer.parseInt(y[i]); } for (int i = 0; i < numCCoeff; i++) { CbCoeff[i] = Integer.parseInt(cb[i]); CrCoeff[i] = Integer.parseInt(cr[i]); } } */ /** * Provides a much faster way of serialization. * * @return a byte array that can be read with the corresponding method. * @see net.semanticmetadata.lire.imageanalysis.CEDD#setByteArrayRepresentation(byte[]) */ public byte[] getByteArrayRepresentation() { byte[] result = new byte[2 * 4 + numYCoeff * 4 + 2 * numCCoeff * 4]; System.arraycopy(SerializationUtils.toBytes(numYCoeff), 0, result, 0, 4); System.arraycopy(SerializationUtils.toBytes(numCCoeff), 0, result, 4, 4); System.arraycopy(SerializationUtils.toByteArray(YCoeff), 0, result, 8, numYCoeff * 4); System.arraycopy(SerializationUtils.toByteArray(CbCoeff), 0, result, numYCoeff * 4 + 8, numCCoeff * 4); System.arraycopy(SerializationUtils.toByteArray(CrCoeff), 0, result, numYCoeff * 4 + numCCoeff * 4 + 8, numCCoeff * 4); return result; } /** * Reads descriptor from a byte array. Much faster than the String based method. * * @param in byte array from corresponding method * @see net.semanticmetadata.lire.imageanalysis.CEDD#getByteArrayRepresentation */ public void setByteArrayRepresentation(byte[] in) { int[] data = SerializationUtils.toIntArray(in); numYCoeff = data[0]; numCCoeff = data[1]; YCoeff = new int[numYCoeff]; CbCoeff = new int[numCCoeff]; CrCoeff = new int[numCCoeff]; System.arraycopy(data, 2, YCoeff, 0, numYCoeff); System.arraycopy(data, 2 + numYCoeff, CbCoeff, 0, numCCoeff); System.arraycopy(data, 2 + numYCoeff + numCCoeff, CrCoeff, 0, numCCoeff); } public double[] getDoubleHistogram() { double[] result = new double[numYCoeff + numCCoeff * 2]; for (int i = 0; i < numYCoeff; i++) { result[i] = YCoeff[i]; } for (int i = 0; i < numCCoeff; i++) { result[i + numYCoeff] = CbCoeff[i]; result[i + numCCoeff + numYCoeff] = CrCoeff[i]; } return result; } /** * Compares one descriptor to another. * * @param descriptor * @return the distance from [0,infinite) or -1 if descriptor type does not match */ public float getDistance(LireFeature descriptor) { if (!(descriptor instanceof ColorLayoutImpl)) return -1f; ColorLayoutImpl cl = (ColorLayoutImpl) descriptor; return (float) ColorLayoutImpl.getSimilarity(YCoeff, CbCoeff, CrCoeff, cl.YCoeff, cl.CbCoeff, cl.CrCoeff); } }
ColorLayout类继承了ColorLayoutImpl类,同时实现了LireFeature接口。其中的方法大部分都是实现了LireFeature接口的方法。先来看看LireFeature接口是什么样子的:
注:这里没有注释了,仅能靠自己的理解了。
/** * This is the basic interface for all content based features. It is needed for GenericDocumentBuilder etc. * Date: 28.05.2008 * Time: 14:44:16 * * @author Mathias Lux, mathias@juggle.at */ public interface LireFeature { public void extract(BufferedImage bimg); public byte[] getByteArrayRepresentation(); public void setByteArrayRepresentation(byte[] in); public double[] getDoubleHistogram(); float getDistance(LireFeature feature); java.lang.String getStringRepresentation(); void setStringRepresentation(java.lang.String s); }
我简要概括一下自己对这些接口函数的理解:
1.extract(BufferedImage bimg):提取特征向量
2.getByteArrayRepresentation():获取特征向量(返回byte[]类型)
3.setByteArrayRepresentation(byte[] in):设置特征向量(byte[]类型)
4.getDoubleHistogram():
5.getDistance(LireFeature feature):
6.getStringRepresentation():获取特征向量(返回String类型)
7.setStringRepresentation(java.lang.String s):设置特征向量(String类型)
其中咖啡色的是建立索引的过程中会用到的。
看代码的过程中发现,所有的算法都实现了LireFeature接口,如下图所示:
不再研究LireFeature接口,回过头来本来想看看ColorLayoutImpl类,但是没想到代码其长无比,都是些算法,暂时没有这个耐心了,以后有机会再看吧。以下贴出个简略版的。注意:该类中实现了extract(BufferedImage bimg)方法。其他方法例如getByteArrayRepresentation()则在ColorLayout中实现。
package net.semanticmetadata.lire.imageanalysis.mpeg7; import java.awt.image.BufferedImage; import java.awt.image.WritableRaster; /** * Class for extrcating & comparing MPEG-7 based CBIR descriptor ColorLayout * * @author Mathias Lux, mathias@juggle.at */ public class ColorLayoutImpl { // static final boolean debug = true; protected int[][] shape; protected int imgYSize, imgXSize; protected BufferedImage img; protected static int[] availableCoeffNumbers = {1, 3, 6, 10, 15, 21, 28, 64}; public int[] YCoeff; public int[] CbCoeff; public int[] CrCoeff; protected int numCCoeff = 28, numYCoeff = 64; protected static int[] arrayZigZag = { 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, 57, 50, 43, 36, 29, 22, 15, 23, 30, 37, 44, 51, 58, 59, 52, 45, 38, 31, 39, 46, 53, 60, 61, 54, 47, 55, 62, 63 }; ... public void extract(BufferedImage bimg) { this.img = bimg; imgYSize = img.getHeight(); imgXSize = img.getWidth(); init(); } ... }
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