Comparing Images with reference images OpenCV -

i have been working on basic gesture control algorithm. have set of reference images (commands) , sample images (drawn user). want compare sample image reference images , see command has user tried enter (assuming draw/ try draw provided gestures).

however, unable generate concrete matching algorithm. have tried matchshapes opencv library , correlation function well. far, correlation function has provided decent results.

here code

#include<iostream> #include<opencv2/highgui.hpp> #include<opencv2/imgproc.hpp> #include<opencv2/core.hpp>  using namespace std; using namespace cv;  void cannythreshold(mat* src, mat* detect) {     blur(*src, *detect, size(3, 3));     canny(*detect, *detect, 5, 15, 3); }  double correlation(cv::mat &image_1, cv::mat &image_2) {     // convert data-type "float"     cv::mat im_float_1;     image_1.convertto(im_float_1, cv_32f);     cv::mat im_float_2;     image_2.convertto(im_float_2, cv_32f);     int n_pixels = im_float_1.rows * im_float_1.cols;     // compute mean , standard deviation of both images     cv::scalar im1_mean, im1_std, im2_mean, im2_std;     meanstddev(im_float_1, im1_mean, im1_std);     meanstddev(im_float_2, im2_mean, im2_std);     assert(im_float_1.size() == im_float_2.size());     // compute covariance , correlation coefficient     double covar = (im_float_1 - im1_mean).dot(im_float_2 - im2_mean) / n_pixels;     //cout << "correl function conversion \n";     double correl = covar / (im1_std[0] * im2_std[0]);     return correl; }  int main() {     mat src_a, src_b;     src_a = imread("../data/ref_sq.png", 0);     src_b = imread("../data/drawn_sq.png", 0);     assert( !(src_a.empty() || src_b.empty() ) );     namedwindow("ref", window_autosize);     namedwindow("drawn", window_autosize);      mat mata, matb;     rect boundrecta, boundrectb;     cannythreshold(&src_a, &mata);     cannythreshold(&src_b, &matb);      //draw rectangles around gesture (seperate black bkg)     boundrecta = boundingrect(mata);     boundrectb = boundingrect(matb);     rectangle(mata, boundrecta, scalar(255, 0, 0));     rectangle(matb, boundrectb, scalar(255, 0, 0));     mat cropa, cropb;      //resize gesture images same size      cropa = mata(boundrecta);     cropb = matb(boundrectb);     resize(cropa, mata, size(300, 300));     resize(cropb, matb, size(300, 300));     imshow("ref", mata);     imshow("drawn", matb);     double d = correlation(mata, matb);     float variance = matchshapes(mata, matb, cv_tm_ccorr, 0.0);     cout << "variance = " << variance << "\n";     cout << "correlation : " << d << "\n";     waitkey(0);     return 0; } 

i have tried combinations of : square , triangle , circle far. here results these combinations variation = 0 100% match , correlation = 1 100% match.

reference_triangle , drawn_circle  variance : 0.117478   correlation : 0.450111 reference_triangle , drawn_triangle variance : 0.146981   correlation : 0.506216 reference_triangle , drawn_square variance : 0.133144   correlation : 0.449743  reference_square , drawn_circle variance : 0.0244948  correlation : 0.478725 reference_square , drawn_triangle variance : 0.00500868 correlation : 0.410928 reference_square , drawn_square variance : 0.00882819 correlation : 0.512346  reference_circle , drawn_circle variance : 0.0298134  correlation : 0.543662 reference_circle , drawn_triangle variance : 0.00030983 correlation : 0.402365 reference_circle , drawn_square variance : 0.0141467  correlation : 0.473818 

so wondering, there other way matching images should try? appreciated.