OCR recognition based on two-dimensional correlation coefficients of matrices

I want to use simple template matching for image recognition.

The pre-processed character picture is matched to a sample picture of A to J, respectively. The most significant results indicate that the character picture can be identified.

In practice, I used the OpenCV matchtemplate () function, but I didn't get the effect I wanted.

The function of Matchtemplate () is to search for the specified template in the image, if the template is intercepted from the image to be searched, it will have a good effect. But if the template isn't part of the image you're looking for, it doesn't seem to be the effect I want.

After trying the CORR2 () of Matlab, I found that corr2 can solve my problem well.

Double Card::corr2 (Mat MatA, Mat MATB) {//calculates two two-dimensional correlation coefficients for the same size matrix double corr2 = 0;double Amean2 = 0; Double Bmean2 = 0;for (int m = 0; M < mata.rows;  m++) {uchar* dataa = mata.ptr<uchar> (m); uchar* datab = matb.ptr<uchar> (m);  for (int n = 0; n < mata.cols;n++) {Amean2 = Amean2 + dataa[n];                    Bmean2 = Bmean2 + datab[n];} }amean2 = Amean2/(mata.rows * mata.cols);  Bmean2 = Bmean2/(matb.rows * matb.cols);d ouble Cov = 0;double ASTD = 0;double bstd = 0;for (int m = 0; m < mata.rows;  m++) {uchar* dataa = mata.ptr<uchar> (m); uchar* datab = matb.ptr<uchar> (m); for (int n = 0; n < mata.cols;n++) {//Covariance Cov = Cov + (Dataa[n]-Amean2) * (Datab[n]-Bmean2);//a variance Astd = Astd + (da                    Taa[n]-Amean2) * (Dataa[n]-Amean2);//b Variance bstd = Bstd + (Datab[n]-Bmean2) * (Datab[n]-Bmean2);} }CORR2 = Cov/(sqrt (ASTD * bstd)); return CORR2;}

image to be searched mat Srcimage = Imread ("m:/image processing experiment/verification Code/byx001.bmp", 1); Mat Resizemat = Mat::zeros (+, CV_8UC3);//matrix scaled to 25*25. Because the template size to be related matches is 25*25resize (Srcimage,resizemat,resizemat.size ());//correlation match double ccorrval[26] = {0};d ouble max = 0;int Count = 0;for (int m = 0; m <; m++) {char recogpath[100] = {1};strcpy (Recogpath, "m://image Processing experiment//verification code//capital Letter//"); Char num[2 ] = {1};num[0] = + m;strcat (recogpath, num); strcat (Recogpath, ". bmp"); Mat Img_display;resizemat.copyto (Img_display); Mat std = imread (recogpath,0); Mat RESIZEMATSTD = Mat::zeros (+, cv_8uc3); Resize (std,resizematstd,resizematstd.size ()); Adaptivethreshold ( RESIZEMATSTD, RESIZEMATSTD, 255, Adaptive_thresh_mean_c, thresh_binary,5,1); Corr2val[m] = CORR2 (resizeMatSTD,img_ Display), if (Max <= corr2val[m]) {max = Corr2val[m];count = m;}} Char pathname[100]={1};strcpy (pathname, "m://image Processing experiment//Verification Code//test//character _"); Char num[10];_itoa (i, NUM, ten); Strcat ( pathname, num); char c[2] = {1}; C[0] = + count;strcat (pathname, C); strcat (Pathname, ". bmp"); Imwrite (PAthname, Resizemat); 

Character templates:

Recognition result output:

OCR recognition based on two-dimensional correlation coefficients of matrices