=====================================================

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]

=====================================================

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();
    }
	...
}

LIRe 源代码分析 5:提取特征向量[以颜色布局为例]的更多相关文章

  1. LIRe 源代码分析 7:算法类[以颜色布局为例]

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

    ===================================================== 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 ...

  3. LIRe 源代码分析 4:建立索引(DocumentBuilder)[以颜色布局为例]

    ===================================================== LIRe源代码分析系列文章列表: LIRe 源代码分析 1:整体结构 LIRe 源代码分析 ...

  4. LIRe 源代码分析 3:基本接口(ImageSearcher)

    ===================================================== 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 ...

  5. LIRe 源代码分析 2:基本接口(DocumentBuilder)

    ===================================================== 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 ...

  6. LIRe 源代码分析 1:整体结构

    ===================================================== 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 ...

  7. 转:LIRe 源代码分析

    1:整体结构 LIRE(Lucene Image REtrieval)提供一种的简单方式来创建基于图像特性的Lucene索引.利用该索引就能够构建一个基于内容的图像检索(content- based ...

  8. 转:ffdshow 源代码分析

    ffdshow神奇的功能:视频播放时显示运动矢量和QP FFDShow可以称得上是全能的解码.编码器.最初FFDShow只是mpeg视频解码器,不过现在他能做到的远不止于此.它能够解码的视频格式已经远 ...

  9. K-近邻算法的Python实现 : 源代码分析

    网上介绍K-近邻算法的样例非常多.其Python实现版本号基本都是来自于机器学习的入门书籍<机器学习实战>,尽管K-近邻算法本身非常easy,但非常多刚開始学习的人对其Python版本号的 ...

随机推荐

  1. 23 服务的绑定启动Demo3

    MainActivity.java package com.example.day23_service_demo3; import com.example.day23_service_demo3.My ...

  2. Apache shiro集群实现 (六)分布式集群系统下的高可用session解决方案---Session共享

    Apache shiro集群实现 (一) shiro入门介绍 Apache shiro集群实现 (二) shiro 的INI配置 Apache shiro集群实现 (三)shiro身份认证(Shiro ...

  3. 关于bootstrap在IE8下不能支持自适应的问题

    说到这个问题,我就想吐槽下IE了,开发这么多版本,每个版本都有一些这样那样的问题不支持,别的正常的浏览器咋都能支持呢?真是垃圾浏览器!!!! 说归说,但是IE现在用的人多啊,怎么办?这个问题还是得解决 ...

  4. [tornado]使用webscoket的使用总是403错误

    使用的tornado版本为4.0+ 后台: PS D:\CodeHouse\tornado\websocket> python .\ws_app.py WARNING:tornado.acces ...

  5. [error]error while loading shared libraries: libpcre.so.1 解决

    nginx 安装好之后,启动的时候报错 [root@localhost nginx-1.6.2]# /usr/local/nginx/sbin/nginx  /usr/local/nginx/sbin ...

  6. iOS编程Cookbook第19章最后一个例子不能正常工作的解决办法

    大熊猫猪·侯佩原创或翻译作品.欢迎转载,转载请注明出处. 如果觉得写的不好请多提意见,如果觉得不错请多多支持点赞.谢谢! hopy ;) 在Cookbook的第19章的11节中所要解决的是在App中显 ...

  7. 使用github搭建网站

    http://blog.csdn.net/pipisorry/article/details/51707366 使用github建站 github设计了Pages功能,允许用户自定义项目首页,用来替代 ...

  8. 02_c3p0之c3p0-config.xml配置案例,操作c3p0的jdbcUtil工具类的编写

     c3p0也是一个开源jdbc连接池,我们熟悉的Hibernate和Spring框架使用的都是该数据源. 这里获得数据源使用的方法是:ComboPooledDataSource 它提供的构造方法有 ...

  9. FFmpeg的H.264解码器源代码简单分析:解析器(Parser)部分

    ===================================================== H.264源代码分析文章列表: [编码 - x264] x264源代码简单分析:概述 x26 ...

  10. sql中InnoDB和MyISAM的区别

    InnoDB和MyISAM是许多人在使用MySQL时最常用的两个表类型 1,MyISAM类型的表强调的是性能,其执行数度比InnoDB类型更快,但是不提供事务支持等高级处理,往往被认为只适合小项目:而 ...