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Chapter 2 ■ Edge-Detection Techniques 59

/* Convolution of source image with a Gaussian in X and Y directions */
smx = f2d (im->info->nr, im->info->nc);
printf (“Convolution with LoG:\n“);
convolution (im, lgau, n, n, smx, im->info->nr, im->info->nc);

/* Locate the zero crossings */
printf (“Zero crossings:\n“);
zero_cross (smx, im);

/* Clear the boundary */
for (i=0; i<im->info->nr; i++)
{
for (j=0; j<=width; j++) im->data[i][j] = 0;
for (j=im->info->nc-width-1; j<im->info->nc; j++)
im->data[i][j] = 0;
}
for (j=0; j<im->info->nc; j++)
{
for (i=0; i<= width; i++) im->data[i][j] = 0;
for (i=im->info->nr-width-1; i<im->info->nr; i++)
im->data[i][j] = 0;
}

free(smx[0]); free(smx);
free(lgau[0]); free(lgau);
}

/* Gaussian */
float gauss(float x, float sigma)
{
return (float)exp((double) ((-x*x)/(2*sigma*sigma)));
}

float meanGauss (float x, float sigma)
{
float z;
z = (gauss(x,sigma)+gauss(x+0.5,sigma)+gauss(x-0.5,sigma))/3.0;
z = z/(PI*2.0*sigma*sigma);
return z;
}

float LoG (float x, float sigma)
{
float x1;

x1 = gauss (x, sigma);
return (x*x-2*sigma*sigma)/(sigma*sigma*sigma*sigma) * x1;
}