/** Returns reflected version of a matrix */
const math::matrix<float> Convolution::reflection(const math::matrix<float> A)
{
int size = A.rowno();
math::matrix<float> C(size, size);
int col = A.colno();
int row = A.rowno();
for (int x = 0; x < row; x++){
for (int y = 0; y < col; y++){
C((size - 1 - x), (size - 1 - y)) = A(x, y);
}
}
return C;
}
/** Joins to matrices by multiplying the A[i,j] with B[i,j].
* Warning! Both Matrices must be squares with the same size!
*/
const math::matrix<float> Convolution::join(math::matrix<float> A, math::matrix<float> B)
{
int size = A.rowno();
math::matrix<float> C(size, size);
for(int x=0; x<size; x++){
for(int y=0; y<size; y++) {
C(x, y) = A(x, y) * B(x, y);
}
}
return C;
}
/** Sums all of the matrixes elements */
const float Convolution::sum(const math::matrix<float> A)
{
float sum = 0.0;
int col = A.colno();
int row = A.rowno();
for(int x=0; x<row; x++){
for(int y=0; y<col; y++){
sum += A(x,y);
}
}
return sum;
}
const int MorphDilate::morph(math::matrix<float> window, math::matrix<bool> se)
{
float min = PIXEL_VAL_MAX+1;
int tempx,tempy;
tempx = window.rowno();
tempy = window.colno();
for(int i=0;i<tempx;i++){
for(int j=0;j<tempy;j++){
if(se(i,j)==true){
if(window(i,j)<min){
min = window(i,j);
}
}
}
}
return (int) min;
}
const int MorphErode::morph(math::matrix<float> window, math::matrix<bool> se)
{
float max=0.0;
int row = se.rowno();
int col = se.colno();
for(int i=0; i<row; i++)
{
for(int j=0; j<col; j++)
{
if(se(i,j)==true && window(i,j)>max)
{
max = window(i,j);
}
}
}
return max;
}
