比较简单的灰度图像模板匹配算法

#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>  
#include <opencv2/imgproc/imgproc.hpp>  
#include <opencv2/core/core.hpp> 
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/flann/flann.hpp>
#include <opencv2/core/ocl.hpp> 
#include <iostream>
#include <string>

using namespace cv;
using namespace cv::ocl;
using namespace std;

void runMatchGrayUseCpu(int method);
void runMatchGrayUseGpu(int method);

int main(int argc, char **argv){

    int method = CV_TM_SQDIFF_NORMED;

    runMatchGrayUseCpu(method);
    runMatchGrayUseGpu(method);

    return 0;
}

void runMatchGrayUseCpu(int method){

    double t = 0.0;

    t = (double)cv::getTickCount();
    // 1.get src image
    cv::Mat src = cv::imread("C:\\Users\\KayChan\\Desktop\\kj_color_detect\\11.bmp", 1);

    // 2.get template image
    cv::Mat tmp = cv::imread("C:\\Users\\KayChan\\Desktop\\testimage\\tmp.png", 1);

    // 3.gray image
    cv::Mat gray_src, gray_tmp;
    if (src.channels() == 1) gray_src = src;
    else cv::cvtColor(src, gray_src, CV_RGB2GRAY);
    if (tmp.channels() == 1) gray_tmp = tmp;
    else cv::cvtColor(tmp, gray_tmp, CV_RGB2GRAY);

    // 4.match
    int result_cols = gray_src.cols - gray_tmp.cols + 1;
    int result_rows = gray_src.rows - gray_tmp.rows + 1;
    cv::Mat result = cv::Mat(result_cols, result_rows, CV_32FC1);
    cv::matchTemplate(gray_src, gray_tmp, result, method);

    cv::Point point;
    double minVal, maxVal;
    cv::Point minLoc, maxLoc;
    cv::minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc, cv::Mat());
    switch (method){

    case CV_TM_SQDIFF:
        point = minLoc;
        break;
    case CV_TM_SQDIFF_NORMED:
        point = minLoc;
        break;
    case CV_TM_CCORR:
    case CV_TM_CCOEFF:
        point = maxLoc;
        break;
    case CV_TM_CCORR_NORMED:
    case CV_TM_CCOEFF_NORMED:
    default:
        point = maxLoc;
        break;
    }
    t = ((double)cv::getTickCount() - t) / cv::getTickFrequency();

    std::cout << "======Test Match Template Use CPU======" << std::endl;
    std::cout << "CPU time :" << t << " second" << std::endl;
    std::cout << "obj.x :" << point.x << " obj.y :" << point.y << std::endl;
    std::cout << " " << std::endl;
}

void runMatchGrayUseGpu(int method){

    double t = 0.0;

    t = (double)cv::getTickCount();
    // 1.get src image
    cv::UMat src = cv::imread("C:\\Users\\KayChan\\Desktop\\kj_color_detect\\11.bmp", 1).getUMat(cv::ACCESS_RW);

    // 2.get template image
    cv::UMat tmp = cv::imread("C:\\Users\\KayChan\\Desktop\\testimage\\tmp.png", 1).getUMat(cv::ACCESS_RW);

    // 3.gray image
    cv::UMat gray_src, gray_tmp;
    if (src.channels() == 1) gray_src = src;
    else cv::cvtColor(src, gray_src, CV_RGB2GRAY);
    if (tmp.channels() == 1) gray_tmp = tmp;
    else cv::cvtColor(tmp, gray_tmp, CV_RGB2GRAY);

    // 4.match
    int result_cols = gray_src.cols - gray_tmp.cols + 1;
    int result_rows = gray_src.rows - gray_tmp.rows + 1;
    cv::UMat result = cv::UMat(result_cols, result_rows, CV_32FC1);
    cv::matchTemplate(gray_src, gray_tmp, result, method);

    cv::Point point;
    double minVal, maxVal;
    cv::Point minLoc, maxLoc;
    cv::minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc, cv::Mat());
    switch (method){

    case CV_TM_SQDIFF:
        point = minLoc;
        break;
    case CV_TM_SQDIFF_NORMED:
        point = minLoc;
        break;
    case CV_TM_CCORR:
    case CV_TM_CCOEFF:
        point = maxLoc;
        break;
    case CV_TM_CCORR_NORMED:
    case CV_TM_CCOEFF_NORMED:
    default:
        point = maxLoc;
        break;
    }
    t = ((double)cv::getTickCount() - t) / cv::getTickFrequency();

    std::cout << "======Test Match Template Use OpenCL======" << std::endl;
    std::cout << "OpenCL time :" << t << " second" << std::endl;
    std::cout << "obj.x :" << point.x << " obj.y :" << point.y << std::endl;
    std::cout << " " << std::endl;
}