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#include <stdio.h>
#include <stdlib.h>
#include <malloc.h>
#include <math.h>
#include <string.h>
#include <unistd.h>
#include <ppm.h>
#include "gabor.h"
/* note that all this is taken from the paper JaH98 in ~/tex/bib/squizz.bib */
/* (with my corrections!) */
static double ***kernel11 = NULL;
static double ***kernel12 = NULL;
static double ***kernel21 = NULL;
static double ***kernel22 = NULL;
static int kernal_size[num_gabor_scales] = {gabor_kernel_size_0, gabor_kernel_size_1, gabor_kernel_size_2};
void save_norm_double_pgm(double *double_im, int w, int h, char *fname) {
PPM *im;
float *norm_im;
int i;
FILE *outfile;
int the_error;
/* copy the image, and then normalise the contrast */
norm_im = (float *)malloc(w*h*sizeof(float));
for (i = 0; i < w*h; i++)
norm_im[i] = (float)double_im[i];
normaliseContrast(norm_im, w*h);
im = new_ppm();
im->type = PGM_RAW;
im->width = w;
im->height = h;
im->max_col_comp = 255;
im->bytes_per_pixel = 1;
im->pixel = (byte *)malloc(w*h*sizeof(byte));
for (i = 0; i < w*h; i++)
im->pixel[i] = (byte)norm_im[i];
outfile = fopen(fname, "wb");
if ((the_error = write_ppm(outfile, im, PGM_RAW)) != PPM_OK) {
ppm_handle_error(the_error);
exit(1);
}
fclose(outfile);
destroy_ppm(&im);
free(norm_im);
}
void create_filter_kernels() {
int i, j, n;
int x, x_c;
double u0, u, v, sigma, theta;
char fname[256];
/* allocate space for all the filter kernels */
kernel11 = (double ***)malloc(num_gabor_scales*sizeof(double **));
kernel12 = (double ***)malloc(num_gabor_scales*sizeof(double **));
kernel21 = (double ***)malloc(num_gabor_scales*sizeof(double **));
kernel22 = (double ***)malloc(num_gabor_scales*sizeof(double **));
for (i = 0; i < num_gabor_scales; i++) {
kernel11[i] = (double **)malloc(num_gabors_per_scale*sizeof(double *));
for (j = 0; j < num_gabors_per_scale; j++)
kernel11[i][j] = (double *)malloc(kernal_size[i]*sizeof(double));
kernel12[i] = (double **)malloc(num_gabors_per_scale*sizeof(double *));
for (j = 0; j < num_gabors_per_scale; j++)
kernel12[i][j] = (double *)malloc(kernal_size[i]*sizeof(double));
kernel21[i] = (double **)malloc(num_gabors_per_scale*sizeof(double *));
for (j = 0; j < num_gabors_per_scale; j++)
kernel21[i][j] = (double *)malloc(kernal_size[i]*sizeof(double));
kernel22[i] = (double **)malloc(num_gabors_per_scale*sizeof(double *));
for (j = 0; j < num_gabors_per_scale; j++)
kernel22[i][j] = (double *)malloc(kernal_size[i]*sizeof(double));
}
/* now set the values of the kernels */
u0 = u00;
for (i = 0; i < num_gabor_scales; i++) {
sigma = sigma_m(u0);
for (j = 0; j < num_gabors_per_scale; j++) {
theta = j*theta_step;
u = u0*cos(theta);
v = u0*sin(theta);
x_c = kernal_size[i]/2; /* since sizes are odd, this gives the
centre value */
for (x = 0; x < kernal_size[i]; x++) {
/* note that x is "y" for kernels 12 and 22 */
kernel11[i][j][x] = (1/(sqrt(2*M_PI)*sigma)*exp(-sq((x - x_c))/(2*sq(sigma)))*cos(2*M_PI*u*(x - x_c)));
kernel12[i][j][x] = (1/(sqrt(2*M_PI)*sigma)*exp(-sq((x - x_c))/(2*sq(sigma)))*cos(2*M_PI*v*(x - x_c)));
kernel21[i][j][x] = (1/(sqrt(2*M_PI)*sigma)*exp(-sq((x - x_c))/(2*sq(sigma)))*sin(2*M_PI*u*(x - x_c)));
kernel22[i][j][x] = (1/(sqrt(2*M_PI)*sigma)*exp(-sq((x - x_c))/(2*sq(sigma)))*sin(2*M_PI*v*(x - x_c)));
}
}
u0 = u0/2;
}
}
void gabor_filter(double *image, int width, int height, int filter_scale, int n_theta, double *output) {
double *conv;
int x, y, t_x, t_y;
int i;
/* create the filter kernels, if it has not already been done */
if (kernel11 == NULL)
create_filter_kernels();
conv = (double *)calloc(width*height, sizeof(double));
/* first convolution */
for (x = 0; x < width; x++) {
for (y = 0; y < height; y++) {
output[y*width + x] = 0; /* might as well be here */
for (t_x = -kernal_size[filter_scale]/2; t_x <= kernal_size[filter_scale]/2; t_x++) {
if (((x - t_x) >= 0) && ((x - t_x) < width)) {
conv[y*width + x] +=
kernel11[filter_scale][n_theta][t_x + kernal_size[filter_scale]/2]*image[y*width+ (x - t_x)];
}
}
}
}
/* second convolution */
for (x = 0; x < width; x++) {
for (y = 0; y < height; y++) {
for (t_y = -kernal_size[filter_scale]/2; t_y <= kernal_size[filter_scale]/2; t_y++) {
if (((y - t_y) >= 0) && ((y - t_y) < height))
output[y*width + x] +=
kernel12[filter_scale][n_theta][t_y + kernal_size[filter_scale]/2]*conv[(y - t_y)*width + x];
}
}
}
for (i = 0; i < width*height; i++)
conv[i] = 0;
/* third convolution */
for (x = 0; x < width; x++) {
for (y = 0; y < height; y++) {
for (t_x = -kernal_size[filter_scale]/2; t_x <= kernal_size[filter_scale]/2; t_x++) {
if (((x - t_x) >= 0) && ((x - t_x) < width)) {
conv[y*width + x] +=
kernel21[filter_scale][n_theta][t_x + kernal_size[filter_scale]/2]*image[y*width + (x - t_x)];
}
}
}
}
/* fourth convolution */
for (x = 0; x < width; x++) {
for (y = 0; y < height; y++) {
for (t_y = -kernal_size[filter_scale]/2; t_y <= kernal_size[filter_scale]/2; t_y++) {
if (((y - t_y) >= 0) && ((y - t_y) < height))
output[y*width + x] -=
kernel22[filter_scale][n_theta][t_y + kernal_size[filter_scale]/2]*conv[(y - t_y)*width + x];
}
}
}
free(conv);
}
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