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/** \file
* \brief Canny Edge Detector
*
* See Copyright Notice in im_lib.h
* $Id: im_canny.cpp,v 1.1 2008/10/17 06:16:33 scuri Exp $
*/
#include <im.h>
#include "im_process_loc.h"
#include <math.h>
#include <stdlib.h>
#include <memory.h>
/* Scale floating point magnitudes to 8 bits */
static float MAG_SCALE;
/* Biggest possible filter mask */
#define MAX_MASK_SIZE 100
static float ** f2d (int nr, int nc);
static float gauss(float x, float sigma);
static float dGauss (float x, float sigma);
static float meanGauss (float x, float sigma);
static void seperable_convolution (const imImage* im, float *gau, int width, float **smx, float **smy);
static void dxy_seperable_convolution (float** im, int nr, int nc, float *gau, int width, float **sm, int which);
static void nonmax_suppress (float **dx, float **dy, imImage* mag);
void imProcessCanny(const imImage* im, imImage* NewImage, float stddev)
{
int width = 1;
float **smx,**smy;
float **dx,**dy;
int i;
float gau[MAX_MASK_SIZE], dgau[MAX_MASK_SIZE];
/* Create a Gaussian and a derivative of Gaussian filter mask */
for(i=0; i<MAX_MASK_SIZE; i++)
{
gau[i] = meanGauss ((float)i, stddev);
if (gau[i] < 0.005)
{
width = i;
break;
}
dgau[i] = dGauss ((float)i, stddev);
}
smx = f2d (im->height, im->width);
smy = f2d (im->height, im->width);
/* Convolution of source image with a Gaussian in X and Y directions */
seperable_convolution (im, gau, width, smx, smy);
MAG_SCALE = 0;
/* Now convolve smoothed data with a derivative */
dx = f2d (im->height, im->width);
dxy_seperable_convolution (smx, im->height, im->width, dgau, width, dx, 1);
free(smx[0]); free(smx);
dy = f2d (im->height, im->width);
dxy_seperable_convolution (smy, im->height, im->width, dgau, width, dy, 0);
free(smy[0]); free(smy);
if (MAG_SCALE)
MAG_SCALE = 255.0f/(1.4142f*MAG_SCALE);
/* Non-maximum suppression - edge pixels should be a local max */
nonmax_suppress (dx, dy, NewImage);
free(dx[0]); free(dx);
free(dy[0]); free(dy);
}
static float norm (float x, float y)
{
return (float) sqrt ( (double)(x*x + y*y) );
}
static float ** f2d (int nr, int nc)
{
float **x, *y;
int i;
x = (float **)calloc ( nr, sizeof (float *) );
if (!x)
return NULL;
y = (float *)calloc ( nr*nc, sizeof (float) );
if (!y)
return NULL;
for (i=0; i<nr; i++)
{
x[i] = y + i*nc;
}
return x;
}
/* Gaussian */
static float gauss(float x, float sigma)
{
return (float)exp((double) ((-x*x)/(2*sigma*sigma)));
}
static float meanGauss (float x, float sigma)
{
float z;
z = (gauss(x,sigma)+gauss(x+0.5f,sigma)+gauss(x-0.5f,sigma))/3.0f;
// z = z/(3.1415f*2.0f*sigma*sigma);
return z;
}
/* First derivative of Gaussian */
static float dGauss (float x, float sigma)
{
// return -x/(sigma*sigma) * gauss(x, sigma);
return -x * gauss(x, sigma);
}
static void seperable_convolution (const imImage* im, float *gau, int width, float **smx, float **smy)
{
int i,j,k, I1, I2, nr, nc;
float x, y;
unsigned char* im_data = (unsigned char*)im->data[0];
nr = im->height;
nc = im->width;
for (i=0; i<nr; i++)
{
for (j=0; j<nc; j++)
{
x = gau[0] * im_data[i*im->width + j]; y = gau[0] * im_data[i*im->width + j];
for (k=1; k<width; k++)
{
I1 = (i+k)%nr; I2 = (i-k+nr)%nr;
y += gau[k]*im_data[I1*im->width + j] + gau[k]*im_data[I2*im->width + j];
I1 = (j+k)%nc; I2 = (j-k+nc)%nc;
x += gau[k]*im_data[i*im->width + I1] + gau[k]*im_data[i*im->width + I2];
}
smx[i][j] = x; smy[i][j] = y;
}
}
}
static void dxy_seperable_convolution (float** im, int nr, int nc, float *gau, int width, float **sm, int which)
{
int i,j,k, I1, I2;
float x;
for (i=0; i<nr; i++)
{
for (j=0; j<nc; j++)
{
x = 0.0;
for (k=1; k<width; k++)
{
if (which == 0)
{
I1 = (i+k)%nr; I2 = (i-k+nr)%nr;
x += -gau[k]*im[I1][j] + gau[k]*im[I2][j];
}
else
{
I1 = (j+k)%nc; I2 = (j-k+nc)%nc;
x += -gau[k]*im[i][I1] + gau[k]*im[i][I2];
}
}
sm[i][j] = x;
if (x > MAG_SCALE)
MAG_SCALE = x;
}
}
}
static unsigned char tobyte(float x)
{
if (x > 255) return 255;
return (unsigned char)x;
}
static void nonmax_suppress (float **dx, float **dy, imImage* mag)
{
int i,j;
float xx, yy, g2, g1, g3, g4, g, xc, yc;
unsigned char* mag_data = (unsigned char*)mag->data[0];
for (i=1; i<mag->height-1; i++)
{
for (j=1; j<mag->width-1; j++)
{
/* Treat the x and y derivatives as components of a vector */
xc = dx[i][j];
yc = dy[i][j];
if (fabs(xc)<0.01 && fabs(yc)<0.01) continue;
g = norm (xc, yc);
/* Follow the gradient direction, as indicated by the direction of
the vector (xc, yc); retain pixels that are a local maximum. */
if (fabs(yc) > fabs(xc))
{
/* The Y component is biggest, so gradient direction is basically UP/DOWN */
xx = (float)(fabs(xc)/fabs(yc));
yy = 1.0;
g2 = norm (dx[i-1][j], dy[i-1][j]);
g4 = norm (dx[i+1][j], dy[i+1][j]);
if (xc*yc > 0.0)
{
g3 = norm (dx[i+1][j+1], dy[i+1][j+1]);
g1 = norm (dx[i-1][j-1], dy[i-1][j-1]);
}
else
{
g3 = norm (dx[i+1][j-1], dy[i+1][j-1]);
g1 = norm (dx[i-1][j+1], dy[i-1][j+1]);
}
}
else
{
/* The X component is biggest, so gradient direction is basically LEFT/RIGHT */
xx = (float)(fabs(yc)/fabs(xc));
yy = 1.0;
g2 = norm (dx[i][j+1], dy[i][j+1]);
g4 = norm (dx[i][j-1], dy[i][j-1]);
if (xc*yc > 0.0)
{
g3 = norm (dx[i-1][j-1], dy[i-1][j-1]);
g1 = norm (dx[i+1][j+1], dy[i+1][j+1]);
}
else
{
g1 = norm (dx[i-1][j+1], dy[i-1][j+1]);
g3 = norm (dx[i+1][j-1], dy[i+1][j-1]);
}
}
/* Compute the interpolated value of the gradient magnitude */
if ( (g > (xx*g1 + (yy-xx)*g2)) && (g > (xx*g3 + (yy-xx)*g4)) )
{
mag_data[i*mag->width + j] = tobyte(g*MAG_SCALE);
}
}
}
}
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