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hog.h
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Mon, Jul 29, 12:24

hog.h
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/*
Copyright (C) 2014 Jerome Revaud
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>
*/
#ifndef ___HOG_H___
#define ___HOG_H___
#include "array_types.h"
/* * * * * * IMAGE SMOOTHING * * * * * * */
/* Smooth an image using a Gaussian filter.
*/
void _smooth_gaussian( UBYTE_image* img, float sigma, UBYTE_image* res, int n_thread );
/* * * * * * GRADIENT COMPUTATIONS * * * * * * */
/* Compute the dx,dy gradient on the image based on a [-1,0,1] mask.
method
=0 : no prior smoothing
=1 : sobel smoothing
*/
void _compute_grad_101( UBYTE_image* img, int method, float_layers* grad, int n_thread );
/* * * * * * pixel-HOG COMPUTATIONS * * * * * * */
/* Compute the Histogram of oriented gradient for each pixel.
Number of orientations is determined by hog->tz;
method determines orientation bining:
=0 : atan + linear interpolation
=1 : fast cos projection
*/
void _compute_hog( float_layers* grad, int method, float_layers* hog, int n_thread );
/* Compute per-pixel HOG of 8 directions using a different pipeline.
The method uses 4 oriented filters extremely simple ([-1,1])
*/
void _compute_hog_8_direct( UBYTE_image* image, float_layers* hog_out, int n_thread );
/* Post-processing of the HOG: cross-orientation inhibition.
for one pixel i and orientation o: hog[i,o] = max(0, hog[i,o] - coef*hog[i,:].mean())
This is useful for HOGs computed from cosinus projection.
*/
void subtract_mean_ori( float_layers* hog, float coef, int n_thread );
/* Pass the gradient image through a sigmoid
lambda v: 2/(1 + exp(-coef*v + offset)) - 1
*/
void sigmoid_array( float_array* img, float coef, float offset, int n_thread );
/* Compute a spatially smoothed version of the HOG.
*/
void smooth_hog_gaussian( float_layers* hog, float smoothing, int n_thread );
#endif

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