package cc.mrbird.febs.mall.test;
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import javax.imageio.ImageIO;
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import java.awt.*;
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import java.awt.color.ColorSpace;
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import java.awt.image.BufferedImage;
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import java.awt.image.ColorConvertOp;
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import java.io.File;
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import java.io.IOException;
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import java.util.Arrays;
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/**
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* 图片是采用phash算法,一共分为四步吧.
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*
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* 1.将图片缩放到16*16大小,这是我们选择的合适的大小,假如宽高不一样,直接将其压到16*16,去掉细节,只保留宏观;
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*
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* 2.图片一共是16*16的,共256个像素,我们将图片进行灰度化,灰度化就是只有黑白灰三种,从白到黑,一共分了255层;
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*
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* 3.灰度化之后将图片进行DCT转换(离散余弦变化),因为为了识别有的图片旋转,这个DCT转换是将图片进行了一种压缩算法;
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*
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* 4.我们对这个算法进行了优化,因为之前是计算像素的均值,我们为了更准确,我们取RGB,rgb一共分为255个像素,我们将255个像素分为16段,如果像素大于0-16记为0,17到32记为1,直到255,这样就得到255位的二进制,这就是这张图片的指纹码.
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*
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* 得到唯一标识的指纹码之后怎么去计算像素度呢?
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*
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* 通过汉明距离比较两个二进制距离,如果距离小于<10的话,我们就判定两张图片相似.如果两个指纹码(二进制)一模一样,我们就判定两个是一张图片,或者类似;
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*/
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/**
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* 视频相似度算法:
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* 视频的话我们是通过ffmpeg(ff am pig),它是一个专门处理视频的框架,可以从视频中按针提取图片.然后就按照图片的相似度取对比了...
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*/
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/**
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* https://blog.csdn.net/weixin_34095889/article/details/91923072?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522171652008316800182787012%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=171652008316800182787012&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~first_rank_ecpm_v1~rank_v31_ecpm-4-91923072-null-null.142^v100^pc_search_result_base8&utm_term=java%20%E6%8A%8A%E5%9B%BE%E7%89%87%E8%BD%AC%E6%8D%A2%E6%88%90%E9%BB%91%E7%99%BD%E7%81%B0%E5%83%8F%E7%B4%A0%E9%A3%8E%E6%A0%BC&spm=1018.2226.3001.4187
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* 均值哈希实现图像指纹比较
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*/
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public class FingerPrint {
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public static void main(String[] args) {
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FingerPrint fp1 = null;
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FingerPrint fp2 = null;
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try {
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fp1 = new FingerPrint(ImageIO.read(new File("D:\\image\\F1.png")));
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fp2 = new FingerPrint(ImageIO.read(new File("D:\\image\\Z1.jpg")));
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} catch (IOException e) {
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e.printStackTrace();
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}
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System.out.println(fp1.toString(false));
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System.out.println(fp2.toString(false));
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System.out.printf("sim=%f",fp1.compare(fp2));
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}
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/**
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* 图像指纹的尺寸,将图像resize到指定的尺寸，来计算哈希数组
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*/
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private static final int HASH_SIZE=16;
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/**
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* 保存图像指纹的二值化矩阵
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*/
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private final byte[] binaryzationMatrix;
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public FingerPrint(byte[] hashValue) {
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if(hashValue.length!=HASH_SIZE*HASH_SIZE)
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throw new IllegalArgumentException(String.format("length of hashValue must be %d",HASH_SIZE*HASH_SIZE ));
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this.binaryzationMatrix=hashValue;
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}
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public FingerPrint(String hashValue) {
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this(toBytes(hashValue));
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}
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public FingerPrint (BufferedImage src){
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this(hashValue(src));
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}
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private static byte[] hashValue(BufferedImage src){
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BufferedImage hashImage = resize(src,HASH_SIZE,HASH_SIZE);
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byte[] matrixGray = (byte[]) toGray(hashImage).getData().getDataElements(0, 0, HASH_SIZE, HASH_SIZE, null);
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return binaryzation(matrixGray);
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}
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/**
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* 从压缩格式指纹创建{@link FingerPrint}对象
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* @param compactValue
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* @return
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*/
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public static FingerPrint createFromCompact(byte[] compactValue){
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return new FingerPrint(uncompact(compactValue));
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}
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public static boolean validHashValue(byte[] hashValue){
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if(hashValue.length!=HASH_SIZE)
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return false;
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for(byte b:hashValue){
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if(0!=b&&1!=b)return false;
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}
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return true;
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}
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public static boolean validHashValue(String hashValue){
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if(hashValue.length()!=HASH_SIZE)
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return false;
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for(int i=0;i<hashValue.length();++i){
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if('0'!=hashValue.charAt(i)&&'1'!=hashValue.charAt(i))return false;
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}
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return true;
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}
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public byte[] compact(){
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return compact(binaryzationMatrix);
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}
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/**
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* 指纹数据按位压缩
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* @param hashValue
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* @return
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*/
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private static byte[] compact(byte[] hashValue){
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byte[] result=new byte[(hashValue.length+7)>>3];
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byte b=0;
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for(int i=0;i<hashValue.length;++i){
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if(0==(i&7)){
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b=0;
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}
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if(1==hashValue[i]){
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b|=1<<(i&7);
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}else if(hashValue[i]!=0)
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throw new IllegalArgumentException("invalid hashValue,every element must be 0 or 1");
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if(7==(i&7)||i==hashValue.length-1){
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result[i>>3]=b;
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}
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}
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return result;
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}
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/**
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* 压缩格式的指纹解压缩
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* @param compactValue
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* @return
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*/
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private static byte[] uncompact(byte[] compactValue){
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byte[] result=new byte[compactValue.length<<3];
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for(int i=0;i<result.length;++i){
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if((compactValue[i>>3]&(1<<(i&7)))==0)
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result[i]=0;
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else
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result[i]=1;
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}
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return result;
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}
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/**
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* 字符串类型的指纹数据转为字节数组
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* @param hashValue
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* @return
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*/
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private static byte[] toBytes(String hashValue){
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hashValue=hashValue.replaceAll("\\s", "");
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byte[] result=new byte[hashValue.length()];
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for(int i=0;i<result.length;++i){
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char c = hashValue.charAt(i);
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if('0'==c)
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result[i]=0;
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else if('1'==c)
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result[i]=1;
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else
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throw new IllegalArgumentException("invalid hashValue String");
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}
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return result;
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}
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/**
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* 缩放图像到指定尺寸
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* @param src
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* @param width
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* @param height
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* @return
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*/
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private static BufferedImage resize(Image src,int width,int height){
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BufferedImage result = new BufferedImage(width, height,
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BufferedImage.TYPE_3BYTE_BGR);
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Graphics g = result.getGraphics();
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try{
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g.drawImage(src.getScaledInstance(width, height, Image.SCALE_SMOOTH), 0, 0, null);
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}finally{
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g.dispose();
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}
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return result;
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}
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/**
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* 计算均值
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* @param src
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* @return
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*/
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private static int mean(byte[] src){
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long sum=0;
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// 将数组元素转为无符号整数
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for(byte b:src)sum+=(long)b&0xff;
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return (int) (Math.round((float)sum/src.length));
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}
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/**
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* 二值化处理
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* @param src
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* @return
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*/
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private static byte[] binaryzation(byte[]src){
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byte[] dst = src.clone();
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int mean=mean(src);
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for(int i=0;i<dst.length;++i){
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// 将数组元素转为无符号整数再比较
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dst[i]=(byte) (((int)dst[i]&0xff)>=mean?1:0);
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}
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return dst;
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}
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/**
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* 转灰度图像
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* @param src
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* @return
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*/
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private static BufferedImage toGray(BufferedImage src){
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if(src.getType()==BufferedImage.TYPE_BYTE_GRAY){
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return src;
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}else{
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// 图像转灰
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BufferedImage grayImage = new BufferedImage(src.getWidth(), src.getHeight(),
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BufferedImage.TYPE_BYTE_GRAY);
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new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_GRAY), null).filter(src, grayImage);
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return grayImage;
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}
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}
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@Override
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public String toString() {
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return toString(true);
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}
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/**
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* @param multiLine 是否分行
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* @return
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*/
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public String toString(boolean multiLine) {
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StringBuffer buffer=new StringBuffer();
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int count=0;
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for(byte b:this.binaryzationMatrix){
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buffer.append(0==b?'0':'1');
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if(multiLine&&++count%HASH_SIZE==0)
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buffer.append('\n');
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}
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return buffer.toString();
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}
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@Override
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public boolean equals(Object obj) {
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if(obj instanceof FingerPrint){
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return Arrays.equals(this.binaryzationMatrix,((FingerPrint)obj).binaryzationMatrix);
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}else
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return super.equals(obj);
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}
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/**
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* 与指定的压缩格式指纹比较相似度
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* @param compactValue
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* @return
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* @see #compare(FingerPrint)
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*/
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public float compareCompact(byte[] compactValue){
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return compare(createFromCompact(compactValue));
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}
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/**
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* @param hashValue
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* @return
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* @see #compare(FingerPrint)
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*/
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public float compare(String hashValue){
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return compare(new FingerPrint(hashValue));
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}
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/**
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* 与指定的指纹比较相似度
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* @param hashValue
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* @return
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* @see #compare(FingerPrint)
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*/
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public float compare(byte[] hashValue){
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return compare(new FingerPrint(hashValue));
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}
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/**
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* 与指定图像比较相似度
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* @param image2
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* @return
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* @see #compare(FingerPrint)
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*/
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public float compare(BufferedImage image2){
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return compare(new FingerPrint(image2));
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}
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/**
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* 比较指纹相似度
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* @param src
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* @return
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* @see #compare(byte[], byte[])
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*/
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public float compare(FingerPrint src){
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if(src.binaryzationMatrix.length!=this.binaryzationMatrix.length)
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throw new IllegalArgumentException("length of hashValue is mismatch");
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return compare(binaryzationMatrix,src.binaryzationMatrix);
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}
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/**
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* 判断两个数组相似度，数组长度必须一致否则抛出异常
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* @param f1
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* @param f2
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* @return 返回相似度(0.0~1.0)
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*/
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private static float compare(byte[] f1,byte[] f2){
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if(f1.length!=f2.length)
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throw new IllegalArgumentException("mismatch FingerPrint length");
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int sameCount=0;
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for(int i=0;i<f1.length;++i){
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if(f1[i]==f2[i])++sameCount;
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}
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return (float)sameCount/f1.length;
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}
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public static float compareCompact(byte[] f1,byte[] f2){
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return compare(uncompact(f1),uncompact(f2));
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}
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public static float compare(BufferedImage image1,BufferedImage image2){
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return new FingerPrint(image1).compare(new FingerPrint(image2));
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}
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}
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