OpenCV Max locations - opencv

Question

I am working on an OpenCV project and am using cvMatchTemplate to locate part of an image I am then using cvMinMaxLoc to find the maximum area, therefore best match, my problem is that cvMinMaxLoc only returns one max location were as there may be multiple matches in one image.
Is there any way to return all the max locations above a particular threshold
I.e.
for each location > threshold
add location to array
I'm new to OpenCV and dont know if something like this already exists but so far I haven't been able to find anything
Any help greatly appreciated

Answer 1

I modified the matchTemplate tutorial to get you started. It basically uses a queue to track the top X match points, and later plots all of them. Hope that is helpful!
#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;
}

Answer 2

Try cvThreshold(src, dst, threshold, CV_THRESH_BINARY)
This would return an image in dst with all pixels above threshold as white and all others as black. You would then iterate through all the pixels and check if it is greater than 0 then that is a location you want. Something like this
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
}