gaussianMixtureSegmentation.h

#ifndef GAUSSIANMIXTURESEGMENTATION_H
#define GAUSSIANMIXTURESEGMENTATION_H

#include <QImage>
#include "Datapool.h"
#include "ModuleInterface.h"
#include <QDir>
#include "SegmentationTool.h"
#include <opencv2/video/background_segm.hpp>
#include "opencv2/opencv.hpp"

class gaussianMixtureSegmentation : public ModuleInterface
{
public:
    gaussianMixtureSegmentation(Datapool *i_data);
    ~gaussianMixtureSegmentation();

    //Set module configuration parameters
    bool setParameters(QDomNode& config);

    //Initialization after reading parameters
    bool init();

    //Function executed at each frame
    bool run();

    //update parameters at runtime.
    bool updateParameters();

    //Apply Mask
    void applyMask(QImage *current);

private:

    int currentframe; //Current Frame
    bool MOG2;//Set MOG2 Method
    bool defaultMOG2; //Set MOG2 default parameters
    bool m_mask;//Set mask Image
    QString m_maskImName;//Mask Image Name
    SegmentationTool st;

    //Constructor Parameters
    int historyMOG; //Length of the history
    int nmixtures; //Number of Gaussians Mixtures (MOG and MOG2)
    double backgroundRatio; //Threshold of data that should be accounted for by the background (Parámetro T)
    double noiseSigma; //Noise Strength
    float varThreshold; //MOG2 Threshold on the squared Mahalanobis distance to decide whether it is well described by the background model
    bool bShadowDetection; // MOG2 Parameter defining whether shadow detection should be enabled (true or false).
    float varThresholdGen; //MOG2
    float fVarInit; //MOG2
    float fVarMin; //MOG2
    float fVarMax; //MOG2
    float fCT; //MOG2
    float nShadowDetection;
    float fTau;

    double learningRate; //Learning Rate

    cv::Mat frame; //current frame
    cv::Mat resizeF;
    cv::Mat fgMaskMOG;//fg mask generated by MOG method
    cv::Mat bgMOG; //Background Image

    cv::Ptr<cv::BackgroundSubtractorMOG2> mog;

};

#endif // GAUSSIANMIXTURESEGMENTATION_H