opencv3/C++ PHash算法图像检索详解

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

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

DCT变换

Mat srcDCT;

dct(src, srcDCT);

计算DCT左上角8*8像素区域均值,求hash值

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

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。

#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:

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。

以上这篇opencv3/C++ PHash算法图像检索详解就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持。

以上是 opencv3/C++ PHash算法图像检索详解 的全部内容, 来源链接: utcz.com/p/244654.html

回到顶部