OpenCV - Accessing Mat data using for loop

Question

I'm trying to create a convolution function but I'm having trouble during the access to the kernel data (cv::Mat).

I create the 3x3 kernel:

  cv::Mat krn(3, 3, CV_32FC1);
  krn.setTo(1);
  krn = krn/9;

And I try to loop over it. Next the image Mat will be the image to which I want to apply the convolution operator and output will be the result of convolution:

     for (int r = 0; r < image.rows - krn.rows; ++r) {

        for (int c = 0; c < image.cols - krn.cols; ++c) {

        int sum = 0;

        for (int rs = 0; rs < krn.rows; ++rs) {
          for (int cs = 0; cs < krn.cols; ++cs) {

            sum += krn.data[rs * krn.cols + cs] * image.data[(r + rs) * image.cols + c + cs];
          }
        }
        output.data[(r+1)*src.cols + c + 1]=sum;  // assuming 3x3 kernel
    }
  }

However the output is not as desired (only randomic black and white pixel). However, if I change my code this way:

for (int r = 0; r < image.rows - krn.rows; ++r) {
    
            for (int c = 0; c < image.cols - krn.cols; ++c) {
    
            int sum = 0;
    
            for (int rs = 0; rs < krn.rows; ++rs) {
              for (int cs = 0; cs < krn.cols; ++cs) {
    
                sum += 0.11 * image.data[(r + rs) * image.cols + c + cs];           // CHANGE HERE
              }
            }
            output.data[(r+1)*src.cols + c + 1]=sum;  // assuming 3x3 kernel
        }
      }

Using 0.11 instead of the kernel values seems to give the correct output. For this reason I think I'm doing something wrong accessing the kernel's data.

PS: I cannot use krn.at<float>(rs,cs) .

Thanks!

Answer 1

cv::Mat::data is pointer of type uchar .

By data[y * cols + x] you access some byte of stored float values in krn . To get full float values use at method template:

krn.at<float>(rs,cs)

Consider changing type of sum variable to be real. Without this, you may lose partial results when calculating convolution .

---

So, if you cannot use at , just read 4 bytes from data pointer:

float v = 0.0;
memcpy(&v, krn.data + (rs * krn.step + cs * sizeof(float)), 4);

step - means total bytes occupied by one line in mat.

Answer 2

Instead of needlessly using memcpy , you can just cast the pointer. I'll use a C-style cast because why not.

cv::Mat krn = 1 / (cv::Mat_<float>(3,3) <<
    1, 2, 3,
    4, 5, 6,
    7, 8, 9);

for (int i = 0; i < krn.rows; i += 1)
{
    for (int j = 0; j < krn.cols; j += 1)
    {
        // to see clearly what's happening
        uint8_t *byteptr = krn.data + krn.step[0] * i + krn.step[1] * j;
        float *floatptr = (float*) byteptr;

        // or in one step:
        float *floatptr = (float*) (krn.data + krn.step[0] * i + krn.step[1] * j);

        cout << "krn_{" << (i+1) << "," << (j+1) << "} = " << (*floatptr) << endl;
    }
}

krn_{1,1} = 1
krn_{1,2} = 0.5
krn_{1,3} = 0.333333
krn_{2,1} = 0.25
krn_{2,2} = 0.2
krn_{2,3} = 0.166667
krn_{3,1} = 0.142857
krn_{3,2} = 0.125
krn_{3,3} = 0.111111

Note that pointer arithmetic may not be obvious. if you have a uint8_t* , adding 1 moves it by one uint8_t , and if you have a float* , adding 1 moves it by one float which is four bytes.

Consult the documentation for details, which include information on the step[] array that contains the strides/steps to calculate the offset given a tuple of indices into the matrix.