LIRe 源代码分析 4：建立索引（DocumentBuilder）[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 1：整体结构

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 5：提取特征向量[以颜色布局为例]

LIRe 源代码分析 6：检索（ImageSearcher）[以颜色布局为例]

LIRe 源代码分析 7：算法类[以颜色布局为例]

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前几篇文章介绍了LIRe 的基本接口。现在来看一看它的实现部分，本文先来看一看建立索引（（DocumentBuilder））部分。不同的特征向量提取方法的建立索引的类各不相同，它们都位于“net.semanticmetadata.lire.impl”中，如下图所示：

由图可见，每一种方法对应一个DocumentBuilder和一个ImageSearcher，类的数量非常的多，无法一一分析。在这里仅分析一个比较有代表性的：颜色布局。

颜色直方图建立索引的类的名称是ColorLayoutDocumentBuilder，该类继承了AbstractDocumentBuilder，它的源代码如下所示：

/* * 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 ([e-mail]) *     http://www.semanticmetadata.net/lire */package net.semanticmetadata.lire.impl;import net.semanticmetadata.lire.AbstractDocumentBuilder;import net.semanticmetadata.lire.DocumentBuilder;import net.semanticmetadata.lire.imageanalysis.ColorLayout;import net.semanticmetadata.lire.utils.ImageUtils;import org.apache.lucene.document.Document;import org.apache.lucene.document.Field;import java.awt.image.BufferedImage;import java.util.logging.Logger;/** * Provides a faster way of searching based on byte arrays instead of Strings. The method * {@link net.semanticmetadata.lire.imageanalysis.ColorLayout#getByteArrayRepresentation()} is used * to generate the signature of the descriptor much faster. * User: Mathias Lux, [e-mail] * Date: 30.06.2011 */public class ColorLayoutDocumentBuilder extends AbstractDocumentBuilder {    private Logger logger = Logger.getLogger(getClass().getName());    public static final int MAX_IMAGE_DIMENSION = 1024;    public Document createDocument(BufferedImage image, String identifier) {        assert (image != null);        BufferedImage bimg = image;        // Scaling image is especially with the correlogram features very important!        // All images are scaled to guarantee a certain upper limit for indexing.        if (Math.max(image.getHeight(), image.getWidth()) > MAX_IMAGE_DIMENSION) {            bimg = ImageUtils.scaleImage(image, MAX_IMAGE_DIMENSION);        }        Document doc = null;        logger.finer("Starting extraction from image [ColorLayout - fast].");        ColorLayout vd = new ColorLayout();        vd.extract(bimg);        logger.fine("Extraction finished [ColorLayout - fast].");        doc = new Document();        doc.add(new Field(DocumentBuilder.FIELD_NAME_COLORLAYOUT_FAST, vd.getByteArrayRepresentation()));        if (identifier != null)            doc.add(new Field(DocumentBuilder.FIELD_NAME_IDENTIFIER, identifier, Field.Store.YES, Field.Index.NOT_ANALYZED));        return doc;    }}

从源代码来看，其实主要就一个函数：createDocument(BufferedImage image, String identifier)，该函数的流程如下所示：

1.如果输入的图像分辨率过大（在这里是大于1024），则将图像缩小。

2.新建一个ColorLayout类型的对象vd。

3.调用vd.extract()提取特征向量。

4.调用vd.getByteArrayRepresentation()获得特征向量。

5.将获得的特征向量加入Document，返回Document。

其实其他方法的DocumentBuilder的实现和颜色直方图的DocumentBuilder差不多。例如CEDDDocumentBuilder的源代码如下所示：

/* * 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 ([e-mail]) *     http://www.semanticmetadata.net/lire */package net.semanticmetadata.lire.impl;import net.semanticmetadata.lire.AbstractDocumentBuilder;import net.semanticmetadata.lire.DocumentBuilder;import net.semanticmetadata.lire.imageanalysis.CEDD;import net.semanticmetadata.lire.utils.ImageUtils;import org.apache.lucene.document.Document;import org.apache.lucene.document.Field;import java.awt.image.BufferedImage;import java.util.logging.Logger;/** * Provides a faster way of searching based on byte arrays instead of Strings. The method * {@link net.semanticmetadata.lire.imageanalysis.CEDD#getByteArrayRepresentation()} is used * to generate the signature of the descriptor much faster. * User: Mathias Lux, [e-mail] * Date: 12.03.2010 * Time: 13:21:35 * * @see GenericFastDocumentBuilder * @deprecated use GenericFastDocumentBuilder instead. */public class CEDDDocumentBuilder extends AbstractDocumentBuilder {    private Logger logger = Logger.getLogger(getClass().getName());    public static final int MAX_IMAGE_DIMENSION = 1024;    public Document createDocument(BufferedImage image, String identifier) {        assert (image != null);        BufferedImage bimg = image;        // Scaling image is especially with the correlogram features very important!        // All images are scaled to guarantee a certain upper limit for indexing.        if (Math.max(image.getHeight(), image.getWidth()) > MAX_IMAGE_DIMENSION) {            bimg = ImageUtils.scaleImage(image, MAX_IMAGE_DIMENSION);        }        Document doc = null;        logger.finer("Starting extraction from image [CEDD - fast].");        CEDD vd = new CEDD();        vd.extract(bimg);        logger.fine("Extraction finished [CEDD - fast].");        doc = new Document();        doc.add(new Field(DocumentBuilder.FIELD_NAME_CEDD, vd.getByteArrayRepresentation()));        if (identifier != null)            doc.add(new Field(DocumentBuilder.FIELD_NAME_IDENTIFIER, identifier, Field.Store.YES, Field.Index.NOT_ANALYZED));        return doc;    }}