/* Vehicle-road segmetnation tools */
/* Last edited on 2016-04-09 11:02:39 by stolfilocal */

#ifndef dsm_segment_H
#define dsm_segment_H

/* Background/vehicle segmentation. */
/* Version of Jan/2016 */

#include <dsm_image.h>

/*Tries to segment the (reduced) image {img} into foreground and
  background, given the (reduced) reference background image {bg} and
  blurred versions {img_blur}, {bg_blur} of them. Stores into the
  weight image {classw} the fuzzy classification of each pixel, as
  background (255) or foreground (0).  All images must have the same
  dimensions. The parameter {lambda} should be the standard deviation
  of the discrepancy between pixels that are background in {img}. */
void dsm_segment_identify_background
  ( dsm_image_t *img, 
    dsm_image_t *img_blur,
    dsm_image_t *bg,
    dsm_image_t *bg_blur, 
    double lambda,
    dsm_image_t *classw
    );

/*Compares image {img} and {bg} at the pixel row {y} column {x} trying
  to eliminate the effect of lighting by comparing the blurred
  versions {img_blur} and {bg_blur}.  Returns in {*d} the discrepancy
  measure and in {*w} the realibity weight of that measure. If {d = 1}
  it means that the image pixel is twice as bright as the background
  pixel, taking into account the local brightness ratio.  Assumes that
  all images have {nx} cols and by {ny} rows.
  */
void dsm_segment_compute_mismatch
  ( uint8_t *img, 
    uint8_t *img_blur,
    uint8_t *bg,
    uint8_t *bg_blur,
    int nx,
    int ny, 
    int x, 
    int y,
    double *d, 
    double *w
    );

#endif