我正在开发一个OpenCV项目并使用cvMatchTemplate来定位图像的一部分然后我使用cvMinMaxLoc来查找最大区域,因此最匹配,我的问题是cvMinMaxLoc只返回一个最大位置,因为可能存在一张图片中有多个匹配。
是否有办法将所有最大位置返回到特定阈值以上
即
对于每个位置>阈 将位置添加到数组
我是OpenCV的新手,不知道这样的事情是否已经存在,但到目前为止我还没有找到任何东西
任何帮助非常感谢
答案 0 :(得分:3)
我修改了matchTemplate
教程以帮助您入门。它基本上使用queue
来跟踪前X个匹配点,然后绘制所有这些匹配点。希望有帮助!
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <iostream>
#include <vector>
#include <limits>
#include <queue>
using namespace cv;
using namespace std;
void maxLocs(const Mat& src, queue<Point>& dst, size_t size)
{
float maxValue = -1.0f * numeric_limits<float>::max();
float* srcData = reinterpret_cast<float*>(src.data);
for(int i = 0; i < src.rows; i++)
{
for(int j = 0; j < src.cols; j++)
{
if(srcData[i*src.cols + j] > maxValue)
{
maxValue = srcData[i*src.cols + j];
dst.push(Point(j, i));
// pop the smaller one off the end if we reach the size threshold.
if(dst.size() > size)
{
dst.pop();
}
}
}
}
}
/// Global Variables
Mat img; Mat templ; Mat result;
string image_window = "Source Image";
string result_window = "Result window";
int match_method;
int max_Trackbar = 5;
/// Function Headers
void MatchingMethod( int, void* );
int main(int argc, char* argv[])
{
/// Load image and template
img = imread( "dogs.jpg", 1 );
templ = imread( "dog_templ.jpg", 1 );
/// Create windows
namedWindow( image_window, CV_WINDOW_AUTOSIZE );
namedWindow( result_window, CV_WINDOW_AUTOSIZE );
/// Create Trackbar
string trackbar_label = "Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED";
createTrackbar( trackbar_label, image_window, &match_method, max_Trackbar, MatchingMethod );
MatchingMethod( 0, 0 );
waitKey(0);
return 0;
}
/**
* @function MatchingMethod
* @brief Trackbar callback
*/
void MatchingMethod( int, void* )
{
/// Source image to display
Mat img_display;
img.copyTo( img_display );
/// Create the result matrix
int result_cols = img.cols - templ.cols + 1;
int result_rows = img.rows - templ.rows + 1;
result.create( result_cols, result_rows, CV_32FC1 );
/// Do the Matching and Normalize
matchTemplate( img, templ, result, match_method );
normalize( result, result, 0, 1, NORM_MINMAX, -1, Mat() );
/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
if( match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED )
{
result = 1.0 - result;
}
// get the top 100 maximums...
queue<Point> locations;
maxLocs(result, locations, 100);
/// Show me what you got
while(!locations.empty())
{
Point matchLoc = locations.front();
rectangle( img_display, matchLoc, Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );
rectangle( result, matchLoc, Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );
locations.pop();
}
imshow( image_window, img_display );
imshow( result_window, result );
return;
}
答案 1 :(得分:0)
尝试cvThreshold(src,dst,threshold,CV_THRESH_BINARY)
这会在dst中返回一个图像,其中所有像素都高于阈值为白色,其他所有像素为黑色。然后,您将遍历所有像素并检查它是否大于0,那么这是您想要的位置。像这样的东西
char* data = dst->imageData;
int size = (dst->height) * (dst->width)
for (int i=0; i<size; i++)
{
if(data[i] > 0)
//copy i into your array
}