opencv3/C++ PHash算法图像检索详解

时间:2021-09-10 23:22:08

PHash算法即感知哈希算法/Perceptual Hash algorithm,计算基于低频的均值哈希.对每张图像生成一个指纹字符串,通过对该字符串比较可以判断图像间的相似度.

PHash算法原理

将图像转为灰度图,然后将图片大小调整为32*32像素并通过DCT变换,取左上角的8*8像素区域。然后计算这64个像素的灰度值的均值。将每个像素的灰度值与均值对比,大于均值记为1,小于均值记为0,得到64位哈希值。

PHash算法实现

将图片转为灰度值

将图片尺寸缩小为32*32

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resize(src, src, Size(32, 32));

DCT变换

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Mat srcDCT;
dct(src, srcDCT);

计算DCT左上角8*8像素区域均值,求hash值

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double sum = 0;
for (int i = 0; i < 8; i++)
 for (int j = 0; j < 8; j++)
  sum += srcDCT.at<float>(i,j);
 
double average = sum/64;
Mat phashcode= Mat::zeros(Size(8, 8), CV_8U);
for (int i = 0; i < 8; i++)
 for (int j = 0; j < 8; j++)
  phashcode.at<char>(i,j) = srcDCT.at<float>(i,j) > average ? 1:0;

hash值匹配

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int d = 0;
for (int n = 0; n < srchash.size[1]; n++)
 if (srchash.at<uchar>(0,n) != dsthash.at<uchar>(0,n)) d++;

即,计算两幅图哈希值之间的汉明距离,汉明距离越大,两图片越不相似。

OpenCV实现

如图在下图中对比各个图像与图person.jpg的汉明距离,以此衡量两图之间的额相似度。

opencv3/C++ PHash算法图像检索详解

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#include <iostream>
#include <stdio.h>
#include <fstream>
#include <io.h>
#include <string>
#include <opencv2\opencv.hpp>
#include <opencv2\core\core.hpp>
#include <opencv2\core\mat.hpp>
using namespace std;
using namespace cv;
int fingerprint(Mat src, Mat* hash);
 
int main()
{
 Mat src = imread("E:\\image\\image\\image\\person.jpg", 0);
 if(src.empty())
 {
  cout << "the image is not exist" << endl;
  return -1;
 }
 Mat srchash, dsthash;
 fingerprint(src, &srchash);
 for(int i = 1; i <= 8; i++)
 {
  string path0 = "E:\\image\\image\\image\\person";
  string number;
  stringstream ss;
  ss << i;
  ss >> number;
  string path = "E:\\image\\image\\image\\person" + number +".jpg";
  Mat dst = imread(path, 0);
  if(dst.empty())
  {
   cout << "the image is not exist" << endl;
   return -1;
  }
  fingerprint(dst, &dsthash);
  int d = 0;
  for (int n = 0; n < srchash.size[1]; n++)
   if (srchash.at<uchar>(0,n) != dsthash.at<uchar>(0,n)) d++;
 
  cout <<"person" << i <<" distance= " <<d<<"\n";
 }
 
 system("pause");
 return 0;
}
 
 
int fingerprint(Mat src, Mat* hash)
{
 resize(src, src, Size(32, 32));
 src.convertTo(src, CV_32F);
 Mat srcDCT;
 dct(src, srcDCT);
 srcDCT = abs(srcDCT);
 double sum = 0;
 for (int i = 0; i < 8; i++)
  for (int j = 0; j < 8; j++)
   sum += srcDCT.at<float>(i,j);
 
 double average = sum/64;
 Mat phashcode= Mat::zeros(Size(8, 8), CV_8U);
 for (int i = 0; i < 8; i++)
  for (int j = 0; j < 8; j++)
   phashcode.at<char>(i,j) = srcDCT.at<float>(i,j) > average ? 1:0;
 
 *hash = phashcode.reshape(0,1).clone();
 return 0;
}

输出汉明距离:

opencv3/C++ PHash算法图像检索详解

可以看出若将阈值设置为20则可将后三张其他图片筛选掉。

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原文链接:https://blog.csdn.net/akadiao/article/details/79779634