opencv/modules/legacy/src/bgfg_common.cpp

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#include "precomp.hpp"

void cvReleaseBGStatModel( CvBGStatModel** bg_model )
{
    if( bg_model && *bg_model && (*bg_model)->release )
        (*bg_model)->release( bg_model );
}

int cvUpdateBGStatModel( IplImage* current_frame,
                        CvBGStatModel*  bg_model,
                        double learningRate )
{
    return bg_model && bg_model->update ? bg_model->update( current_frame, bg_model, learningRate ) : 0;
}


//  Function cvRefineForegroundMaskBySegm preforms FG post-processing based on segmentation
//    (all pixels of the segment will be classified as FG if majority of pixels of the region are FG).
// parameters:
//      segments - pointer to result of segmentation (for example MeanShiftSegmentation)
//      bg_model - pointer to CvBGStatModel structure
CV_IMPL void cvRefineForegroundMaskBySegm( CvSeq* segments, CvBGStatModel*  bg_model )
{
    IplImage* tmp_image = cvCreateImage(cvSize(bg_model->foreground->width,bg_model->foreground->height),
                            IPL_DEPTH_8U, 1);
    for( ; segments; segments = ((CvSeq*)segments)->h_next )
    {
        CvSeq seq = *segments;
        seq.v_next = seq.h_next = NULL;
        cvZero(tmp_image);
        cvDrawContours( tmp_image, &seq, CV_RGB(0, 0, 255), CV_RGB(0, 0, 255), 10, -1);
        int num1 = cvCountNonZero(tmp_image);
        cvAnd(tmp_image, bg_model->foreground, tmp_image);
        int num2 = cvCountNonZero(tmp_image);
        if( num2 > num1*0.5 )
            cvDrawContours( bg_model->foreground, &seq, CV_RGB(0, 0, 255), CV_RGB(0, 0, 255), 10, -1);
        else
            cvDrawContours( bg_model->foreground, &seq, CV_RGB(0, 0, 0), CV_RGB(0, 0, 0), 10, -1);
    }
    cvReleaseImage(&tmp_image);
}



CV_IMPL CvSeq*
cvSegmentFGMask( CvArr* _mask, int poly1Hull0, float perimScale,
                 CvMemStorage* storage, CvPoint offset )
{
    CvMat mstub, *mask = cvGetMat( _mask, &mstub );
    CvMemStorage* tempStorage = storage ? storage : cvCreateMemStorage();
    CvSeq *contours, *c;
    int nContours = 0;
    CvContourScanner scanner;

    // clean up raw mask
    cvMorphologyEx( mask, mask, 0, 0, CV_MOP_OPEN, 1 );
    cvMorphologyEx( mask, mask, 0, 0, CV_MOP_CLOSE, 1 );

    // find contours around only bigger regions
    scanner = cvStartFindContours( mask, tempStorage,
        sizeof(CvContour), CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, offset );

    while( (c = cvFindNextContour( scanner )) != 0 )
    {
        double len = cvContourPerimeter( c );
        double q = (mask->rows + mask->cols)/perimScale; // calculate perimeter len threshold
        if( len < q ) //Get rid of blob if it's perimeter is too small
            cvSubstituteContour( scanner, 0 );
        else //Smooth it's edges if it's large enough
        {
            CvSeq* newC;
            if( poly1Hull0 ) //Polygonal approximation of the segmentation
                newC = cvApproxPoly( c, sizeof(CvContour), tempStorage, CV_POLY_APPROX_DP, 2, 0 );
            else //Convex Hull of the segmentation
                newC = cvConvexHull2( c, tempStorage, CV_CLOCKWISE, 1 );
            cvSubstituteContour( scanner, newC );
            nContours++;
        }
    }
    contours = cvEndFindContours( &scanner );

    // paint the found regions back into the image
    cvZero( mask );
    for( c=contours; c != 0; c = c->h_next )
        cvDrawContours( mask, c, cvScalarAll(255), cvScalarAll(0), -1, CV_FILLED, 8,
            cvPoint(-offset.x,-offset.y));

    if( tempStorage != storage )
    {
        cvReleaseMemStorage( &tempStorage );
        contours = 0;
    }

    return contours;
}

/* End of file. */