java 图片相似度判判断

这阵子发现我的图像数据库中有不少内容一样的图像需要剔除,这些内容一样的图像可能尺寸不一样,通道数也可能不一样(灰度/彩色),如下三张图内容完全一样,只是亮度或色彩通道数不同, 

于是想到了用google或baidu的识图功能所用到的“感知哈希算法”来搜索数据库内容一样的图像。  通过这篇文章搞清楚了“感知哈希算法”的基本原理,  《三种基于感知哈希算法的相似图像检索技术》,发现原理很简单,很适合我等粗人,呵呵,于是在java下实现了这个算法的代码 :

java实现

package net.gdface.image;

import java.awt.Graphics;
import java.awt.Image;
import java.awt.color.ColorSpace;
import java.awt.image.BufferedImage;
import java.awt.image.ColorConvertOp;
import java.util.Arrays;

/**
 * 均值哈希实现图像指纹比较
 * @author guyadong
 *
 */
public final class FingerPrint {
    /**
     * 图像指纹的尺寸,将图像resize到指定的尺寸,来计算哈希数组 
     */
    private static final int HASH_SIZE=16;
    /**
     * 保存图像指纹的二值化矩阵
     */
    private final byte[] binaryzationMatrix;
    public FingerPrint(byte[] hashValue) {
        if(hashValue.length!=HASH_SIZE*HASH_SIZE)
            throw new IllegalArgumentException(String.format("length of hashValue must be %d",HASH_SIZE*HASH_SIZE ));
        this.binaryzationMatrix=hashValue;
    }
    public FingerPrint(String hashValue) {
        this(toBytes(hashValue));
    }
    public FingerPrint (BufferedImage src){
        this(hashValue(src));
    }
    private static byte[] hashValue(BufferedImage src){
        BufferedImage hashImage = resize(src,HASH_SIZE,HASH_SIZE);
        byte[] matrixGray = (byte[]) toGray(hashImage).getData().getDataElements(0, 0, HASH_SIZE, HASH_SIZE, null); 
        return  binaryzation(matrixGray);
    }
    /**
     * 从压缩格式指纹创建{@link FingerPrint}对象
     * @param compactValue
     * @return
     */
    public static FingerPrint createFromCompact(byte[] compactValue){
        return new FingerPrint(uncompact(compactValue));
    }

    public static boolean validHashValue(byte[] hashValue){
        if(hashValue.length!=HASH_SIZE)
            return false;
        for(byte b:hashValue){
            if(0!=b&&1!=b)return false;         
        }
        return true;
    }
    public static boolean validHashValue(String hashValue){
        if(hashValue.length()!=HASH_SIZE)
            return false;
        for(int i=0;i<hashValue.length();++i){
            if('0'!=hashValue.charAt(i)&&'1'!=hashValue.charAt(i))return false;         
        }
        return true;
    }
    public byte[] compact(){
        return compact(binaryzationMatrix);
    }

    /**
     * 指纹数据按位压缩
     * @param hashValue
     * @return
     */
    private static byte[] compact(byte[] hashValue){
        byte[] result=new byte[(hashValue.length+7)>>3];
        byte b=0;
        for(int i=0;i<hashValue.length;++i){
            if(0==(i&7)){
                b=0;
            }
            if(1==hashValue[i]){
                b|=1<<(i&7);
            }else if(hashValue[i]!=0)
                throw new IllegalArgumentException("invalid hashValue,every element must be 0 or 1");
            if(7==(i&7)||i==hashValue.length-1){
                result[i>>3]=b;
            }
        }
        return result;
    }

    /**
     * 压缩格式的指纹解压缩
     * @param compactValue
     * @return
     */
    private static byte[] uncompact(byte[] compactValue){
        byte[] result=new byte[compactValue.length<<3];
        for(int i=0;i<result.length;++i){
            if((compactValue[i>>3]&(1<<(i&7)))==0)
                result[i]=0;
            else
                result[i]=1;
        }
        return result;      
    }
    /**
     * 字符串类型的指纹数据转为字节数组
     * @param hashValue
     * @return
     */
    private static byte[] toBytes(String hashValue){
        hashValue=hashValue.replaceAll("\\s", "");
        byte[] result=new byte[hashValue.length()];
        for(int i=0;i<result.length;++i){
            char c = hashValue.charAt(i);
            if('0'==c)
                result[i]=0;
            else if('1'==c)
                result[i]=1;
            else
                throw new IllegalArgumentException("invalid hashValue String");
        }
        return result;
    }
    /**
     * 缩放图像到指定尺寸
     * @param src
     * @param width
     * @param height
     * @return
     */
    private static BufferedImage resize(Image src,int width,int height){
        BufferedImage result = new BufferedImage(width, height,  
                BufferedImage.TYPE_3BYTE_BGR); 
         Graphics g = result.getGraphics();
         try{
             g.drawImage(src.getScaledInstance(width, height, Image.SCALE_SMOOTH), 0, 0, null);
         }finally{
             g.dispose();
         }
        return result;      
    }
    /**
     * 计算均值
     * @param src
     * @return
     */
    private static  int mean(byte[] src){
        long sum=0;
        // 将数组元素转为无符号整数
        for(byte b:src)sum+=(long)b&0xff;
        return (int) (Math.round((float)sum/src.length));
    }
    /**
     * 二值化处理
     * @param src
     * @return
     */
    private static byte[] binaryzation(byte[]src){
        byte[] dst = src.clone();
        int mean=mean(src);
        for(int i=0;i<dst.length;++i){
            // 将数组元素转为无符号整数再比较
            dst[i]=(byte) (((int)dst[i]&0xff)>=mean?1:0);
        }
        return dst;

    }
    /**
     * 转灰度图像
     * @param src
     * @return
     */
    private static BufferedImage toGray(BufferedImage src){
        if(src.getType()==BufferedImage.TYPE_BYTE_GRAY){
            return src;
        }else{
            // 图像转灰
            BufferedImage grayImage = new BufferedImage(src.getWidth(), src.getHeight(),  
                    BufferedImage.TYPE_BYTE_GRAY);
            new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_GRAY), null).filter(src, grayImage);
            return grayImage;       
        }
    }

    @Override
    public String toString() {
        return toString(true);
    }
    /**
     * @param multiLine 是否分行
     * @return
     */
    public String toString(boolean multiLine) {
        StringBuffer buffer=new StringBuffer();
        int count=0;
        for(byte b:this.binaryzationMatrix){
            buffer.append(0==b?'0':'1');
            if(multiLine&&++count%HASH_SIZE==0)
                buffer.append('\n');
        }
        return buffer.toString();
    }
    @Override
    public boolean equals(Object obj) {
        if(obj instanceof FingerPrint){
            return Arrays.equals(this.binaryzationMatrix,((FingerPrint)obj).binaryzationMatrix);
        }else
            return super.equals(obj);
    }

    /**
     * 与指定的压缩格式指纹比较相似度
     * @param compactValue
     * @return
     * @see #compare(FingerPrint)
     */
    public float compareCompact(byte[] compactValue){
        return compare(createFromCompact(compactValue));
    }
    /**
     * @param hashValue
     * @return
     * @see #compare(FingerPrint)
     */
    public float compare(String hashValue){
        return compare(new FingerPrint(hashValue));
    }
    /**
     * 与指定的指纹比较相似度
     * @param hashValue
     * @return
     * @see #compare(FingerPrint)
     */
    public float compare(byte[] hashValue){
        return compare(new FingerPrint(hashValue));
    }
    /**
     * 与指定图像比较相似度
     * @param image2
     * @return
     * @see #compare(FingerPrint)
     */
    public float compare(BufferedImage image2){
        return compare(new FingerPrint(image2));
    }
    /**
     * 比较指纹相似度
     * @param src
     * @return 
     * @see #compare(byte[], byte[])
     */
    public float compare(FingerPrint src){
        if(src.binaryzationMatrix.length!=this.binaryzationMatrix.length)
            throw new IllegalArgumentException("length of hashValue is mismatch");
        return compare(binaryzationMatrix,src.binaryzationMatrix);
    }
    /**
     * 判断两个数组相似度,数组长度必须一致否则抛出异常
     * @param f1
     * @param f2
     * @return 返回相似度(0.0~1.0)
     */
    private static float compare(byte[] f1,byte[] f2){
        if(f1.length!=f2.length)
            throw new IllegalArgumentException("mismatch FingerPrint length");
        int sameCount=0;
        for(int i=0;i<f1.length;++i){
            if(f1[i]==f2[i])++sameCount;
        }
        return (float)sameCount/f1.length;
    }
    public static float compareCompact(byte[] f1,byte[] f2){
        return compare(uncompact(f1),uncompact(f2));
    }
    public static float compare(BufferedImage image1,BufferedImage image2){
        return new FingerPrint(image1).compare(new FingerPrint(image2));
    }
}

调用示例

junit测试代码

package test;

import java.io.File;
import java.io.IOException;

import javax.imageio.ImageIO;

import org.junit.Test;
import net.gdface.image.FingerPrint;
import net.gdface.image.NotImage;
import net.gdface.image.UnsupportedFormat;

public class TestFingerPrint {

    @Test
    public void testCompare() throws IOException{
        FingerPrint fp1 = new FingerPrint(ImageIO.read(new File("d:\\tmp\\he049-black.jpg")));
        FingerPrint fp2 =new FingerPrint(ImageIO.read(new File("d:\\tmp\\he049-gray.jpg")));
        System.out.println(fp1.toString(true));
        System.out.printf("sim=%f",fp1.compare(fp2));
    }
}

结果越接近1,说明两张图片越相似

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