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AdaptiveMedianBGS.hpp
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AdaptiveMedianBGS.hpp
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/****************************************************************************
*
* 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/>.
*
******************************************************************************/
/****************************************************************************
*
* AdaptiveMedianBGS.hpp
*
* Purpose: Implementation of the simple adaptive median background
* subtraction algorithm described in:
* "Segmentation and tracking of piglets in images"
* by McFarlane and Schofield
*
* Author: Donovan Parks, September 2007
Example:
Algorithms::BackgroundSubtraction::AdaptiveMedianParams params;
params.SetFrameSize(width, height);
params.LowThreshold() = 40;
params.HighThreshold() = 2*params.LowThreshold();
params.SamplingRate() = 7;
params.LearningFrames() = 30;
Algorithms::BackgroundSubtraction::AdaptiveMedianBGS bgs;
bgs.Initalize(params);
******************************************************************************/
#ifndef _ADAPTIVE_MEDIAN_BGS_H_
#define _ADAPTIVE_MEDIAN_BGS_H_
#include "Bgs.hpp"
namespace Algorithms
{
namespace BackgroundSubtraction
{
// --- Parameters used by the Adaptive Median BGS algorithm ---
class AdaptiveMedianParams : public BgsParams
{
public:
unsigned char &LowThreshold() { return m_low_threshold; }
unsigned char &HighThreshold() { return m_high_threshold; }
int &SamplingRate() { return m_samplingRate; }
int &LearningFrames() { return m_learning_frames; }
private:
unsigned char m_low_threshold;
unsigned char m_high_threshold;
int m_samplingRate;
int m_learning_frames;
};
// --- Adaptive Median BGS algorithm ---
class AdaptiveMedianBGS : public Bgs
{
public:
virtual ~AdaptiveMedianBGS() {}
void Initalize(const BgsParams& param);
void InitModel(const RgbImage& data);
void Subtract(int frame_num, const RgbImage& data,
BwImage& low_threshold_mask, BwImage& high_threshold_mask);
void Update(int frame_num, const RgbImage& data, const BwImage& update_mask);
RgbImage* Background();
private:
void SubtractPixel(int r, int c, const RgbPixel& pixel,
unsigned char& low_threshold, unsigned char& high_threshold);
AdaptiveMedianParams m_params;
RgbImage m_median;
};
};
};
#endif