opencv判断两张图片的相似度

opencv 判断两张图片的相似度 - 程序员大本营 (pianshen.com)

Goal

Today it is common to have a digital video recording system at your disposal. Therefore, you will eventually come to the situation that you no longer process a batch of images, but video streams. These may be of two kinds: real-time image feed (in the case of a webcam) or prerecorded and hard disk drive stored files. Luckily OpenCV threats these two in the same manner, with the same C++ class. So here’s what you’ll learn in this tutorial:

  • How to open and read video streams
  • Two ways for checking image similarity: PSNR and SSIM

The source code

As a test case where to show off these using OpenCV I’ve created a small program that reads in two video files and performs a similarity check between them. This is something you could use to check just how well a new video compressing algorithms works. Let there be a reference (original) video like this small Megamind clip and a compressed version of it. You may also find the source code and these video file in the samples/cpp/tutorial_code/HighGUI/video-input-psnr-ssim/ folder of the OpenCV source library.

 

 

#include <iostream> // for standard I/O
#include <string>   // for strings
#include <iomanip>  // for controlling float print precision
#include <sstream>  // string to number conversion

#include <opencv2/core/core.hpp>        // Basic OpenCV structures (cv::Mat, Scalar)
#include <opencv2/imgproc/imgproc.hpp>  // Gaussian Blur
#include <opencv2/highgui/highgui.hpp>  // OpenCV window I/O

using namespace std;
using namespace cv;

double getPSNR ( const Mat& I1, const Mat& I2);
Scalar getMSSIM( const Mat& I1, const Mat& I2);

int main(int argc, char *argv[])
    help();

    if (argc != 5)
    {
        cout << "Not enough parameters" << endl;
        return -1;
    }

    stringstream conv;

    const string sourceReference = argv[1], sourceCompareWith = argv[2];
    int psnrTriggerValue, delay;
    conv << argv[3] << endl << argv[4];       // put in the strings
    conv >> psnrTriggerValue >> delay;        // take out the numbers

    char c;
    int frameNum = -1;          // Frame counter

    VideoCapture captRefrnc(sourceReference), captUndTst(sourceCompareWith);

    if (!captRefrnc.isOpened())
    {
        cout  << "Could not open reference " << sourceReference << endl;
        return -1;
    }

    if (!captUndTst.isOpened())
    {
        cout  << "Could not open case test " << sourceCompareWith << endl;
        return -1;
    }

    Size refS = Size((int) captRefrnc.get(CV_CAP_PROP_FRAME_WIDTH),
                     (int) captRefrnc.get(CV_CAP_PROP_FRAME_HEIGHT)),
         uTSi = Size((int) captUndTst.get(CV_CAP_PROP_FRAME_WIDTH),
                     (int) captUndTst.get(CV_CAP_PROP_FRAME_HEIGHT));

    if (refS != uTSi)
    {
        cout << "Inputs have different size!!! Closing." << endl;
        return -1;
    }

    const char* WIN_UT = "Under Test";
    const char* WIN_RF = "Reference";

    // Windows
    namedWindow(WIN_RF, CV_WINDOW_AUTOSIZE);
    namedWindow(WIN_UT, CV_WINDOW_AUTOSIZE);
    cvMoveWindow(WIN_RF, 400       , 0);         //750,  2 (bernat =0)
    cvMoveWindow(WIN_UT, refS.width, 0);         //1500, 2

    cout << "Reference frame resolution: Width=" << refS.width << "  Height=" << refS.height
         << " of nr#: " << captRefrnc.get(CV_CAP_PROP_FRAME_COUNT) << endl;

    cout << "PSNR trigger value " << setiosflags(ios::fixed) << setprecision(3)
         << psnrTriggerValue << endl;

    Mat frameReference, frameUnderTest;
    double psnrV;
    Scalar mssimV;

    for(;;) //Show the image captured in the window and repeat
    {
        captRefrnc >> frameReference;
        captUndTst >> frameUnderTest;

        if (frameReference.empty() || frameUnderTest.empty())
        {
            cout << " < < <  Game over!  > > > ";
            break;
        }

        ++frameNum;
        cout << "Frame: " << frameNum << "# ";

        ///////////////////////////////// PSNR ////////////////////////////////////////////////////
        psnrV = getPSNR(frameReference,frameUnderTest);
        cout << setiosflags(ios::fixed) << setprecision(3) << psnrV << "dB";

        //////////////////////////////////// MSSIM /////////////////////////////////////////////////
        if (psnrV < psnrTriggerValue && psnrV)
        {
            mssimV = getMSSIM(frameReference, frameUnderTest);

            cout << " MSSIM: "
                << " R " << setiosflags(ios::fixed) << setprecision(2) << mssimV.val[2] * 100 << "%"
                << " G " << setiosflags(ios::fixed) << setprecision(2) << mssimV.val[1] * 100 << "%"
                << " B " << setiosflags(ios::fixed) << setprecision(2) << mssimV.val[0] * 100 << "%";
        }

        cout << endl;

        ////////////////////////////////// Show Image /////////////////////////////////////////////
        imshow(WIN_RF, frameReference);
        imshow(WIN_UT, frameUnderTest);

        c = (char)cvWaitKey(delay);
        if (c == 27) break;
    }

    return 0;
}

double getPSNR(const Mat& I1, const Mat& I2)
{
    Mat s1;
    absdiff(I1, I2, s1);       // |I1 - I2|
    s1.convertTo(s1, CV_32F);  // cannot make a square on 8 bits
    s1 = s1.mul(s1);           // |I1 - I2|^2

    Scalar s = sum(s1);        // sum elements per channel

    double sse = s.val[0] + s.val[1] + s.val[2]; // sum channels

    if( sse <= 1e-10) // for small values return zero
        return 0;
    else
    {
        double mse  = sse / (double)(I1.channels() * I1.total());
        double psnr = 10.0 * log10((255 * 255) / mse);
        return psnr;
    }
}

Scalar getMSSIM( const Mat& i1, const Mat& i2)
{
    const double C1 = 6.5025, C2 = 58.5225;
    /***************************** INITS **********************************/
    int d = CV_32F;

    Mat I1, I2;
    i1.convertTo(I1, d);            // cannot calculate on one byte large values
    i2.convertTo(I2, d);

    Mat I2_2   = I2.mul(I2);        // I2^2
    Mat I1_2   = I1.mul(I1);        // I1^2
    Mat I1_I2  = I1.mul(I2);        // I1 * I2

    /*************************** END INITS **********************************/

    Mat mu1, mu2;                   // PRELIMINARY COMPUTING
    GaussianBlur(I1, mu1, Size(11, 11), 1.5);
    GaussianBlur(I2, mu2, Size(11, 11), 1.5);

    Mat mu1_2   =   mu1.mul(mu1);
    Mat mu2_2   =   mu2.mul(mu2);
    Mat mu1_mu2 =   mu1.mul(mu2);

    Mat sigma1_2, sigma2_2, sigma12;

    GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);
    sigma1_2 -= mu1_2;

    GaussianBlur(I2_2, sigma2_2, Size(11, 11), 1.5);
    sigma2_2 -= mu2_2;

    GaussianBlur(I1_I2, sigma12, Size(11, 11), 1.5);
    sigma12 -= mu1_mu2;

    ///////////////////////////////// FORMULA ////////////////////////////////
    Mat t1, t2, t3;

    t1 = 2 * mu1_mu2 + C1;
    t2 = 2 * sigma12 + C2;
    t3 = t1.mul(t2);                 // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))

    t1 = mu1_2 + mu2_2 + C1;
    t2 = sigma1_2 + sigma2_2 + C2;
    t1 = t1.mul(t2);                 // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))

    Mat ssim_map;
    divide(t3, t1, ssim_map);        // ssim_map =  t3./t1;

    Scalar mssim = mean(ssim_map);   // mssim = average of ssim map


posted on 2023-11-07 16:16  Earvin  阅读(44)  评论(0编辑  收藏  举报

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