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OpenCV:利用Camshift算法进行彩色目标的跟踪

时间:2015-02-11 16:38:54      阅读:353      评论:0      收藏:0      [点我收藏+]

标签:opencv

<span style="font-size:14px;">#include <opencv\cv.h>
#include <opencv\highgui.h>

#include <stdio.h>
#include <ctype.h>

IplImage *image = 0, *hsv = 0, *hue = 0, *mask = 0, *backproject = 0, *histimg = 0;
CvHistogram *hist = 0;

int backproject_mode = 0;
int select_object = 0;
int track_object = 0;
int show_hist = 1;
CvPoint origin;
CvRect selection;
CvRect track_window;
CvBox2D track_box;  // tracking 返回的区域box, 带角度
CvConnectedComp track_comp;
int hdims = 48;     // 划分HIST的个数,越高越精确
float hranges_arr[] = {0,180};
float* hranges = hranges_arr;
int vmin = 10, vmax = 256, smin = 30;

void on_mouse( int event, int x, int y, int flags ){

    if( !image )
        return;

    if( image->origin )
        y = image->height - y;

    if( select_object ){

        selection.x = MIN(x,origin.x);
        selection.y = MIN(y,origin.y);
        selection.width = selection.x + CV_IABS(x - origin.x);
        selection.height = selection.y + CV_IABS(y - origin.y);

        selection.x = MAX( selection.x, 0 );
        selection.y = MAX( selection.y, 0 );
        selection.width = MIN( selection.width, image->width );
        selection.height = MIN( selection.height, image->height );
        selection.width -= selection.x;
        selection.height -= selection.y;

    }

    switch( event ){

    case CV_EVENT_LBUTTONDOWN:
        origin = cvPoint(x,y);
        selection = cvRect(x,y,0,0);
        select_object = 1;
        break;
    case CV_EVENT_LBUTTONUP:
        select_object = 0;
        if( selection.width > 0 && selection.height > 0 )
            track_object = -1;
#ifdef _DEBUG
        printf("\n # 鼠标的选择区域");
        printf("\n   X = %d, Y = %d, Width = %d, Height = %d",
               selection.x, selection.y, selection.width, selection.height);
#endif
        break;
    }
}


CvScalar hsv2rgb( float hue ){

    int rgb[3], p, sector;
    static const int sector_data[][3]=
    {{0,2,1}, {1,2,0}, {1,0,2}, {2,0,1}, {2,1,0}, {0,1,2}};
    hue *= 0.033333333333333333333333333333333f;
    sector = cvFloor(hue);
    p = cvRound(255*(hue - sector));
    p ^= sector & 1 ? 255 : 0;

    rgb[sector_data[sector][0]] = 255;
    rgb[sector_data[sector][1]] = 0;
    rgb[sector_data[sector][2]] = p;

#ifdef _DEBUG
    printf("\n # Convert HSV to RGB");
    printf("\n   HUE = %f", hue);
    printf("\n   R = %d, G = %d, B = %d", rgb[0],rgb[1],rgb[2]);
#endif

    return cvScalar(rgb[2], rgb[1], rgb[0],0);
}

int main( int argc, char** argv )
{
    CvCapture* capture = 0;
    IplImage* frame = 0;

    if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
        capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 );
    else if( argc == 2 )
        capture = cvCaptureFromAVI( argv[1] );

    if( !capture ){

        fprintf(stderr,"Could not initialize capturing...\n");
        return -1;
    }

    printf( "Hot keys: \n"
            "\tESC - quit the program\n"
            "\tc - stop the tracking\n"
            "\tb - switch to/from backprojection view\n"
            "\th - show/hide object histogram\n"
            "To initialize tracking, select the object with mouse\n" );

    //cvNamedWindow( "Histogram", 1 );
    cvNamedWindow( "CamShiftDemo", 1 );
    cvSetMouseCallback( "CamShiftDemo", (CvMouseCallback)on_mouse, NULL ); // on_mouse 自定义事件
    cvCreateTrackbar( "Vmin", "CamShiftDemo", &vmin, 256, 0 );
    cvCreateTrackbar( "Vmax", "CamShiftDemo", &vmax, 256, 0 );
    cvCreateTrackbar( "Smin", "CamShiftDemo", &smin, 256, 0 );

    for(;;){

        int i, bin_w, c;

        frame = cvQueryFrame( capture );
        if( !frame )
            break;

        if( !image ){

            // 分配所有的缓冲区
            image = cvCreateImage( cvGetSize(frame), 8, 3 );
            image->origin = frame->origin;
            hsv = cvCreateImage( cvGetSize(frame), 8, 3 );
            hue = cvCreateImage( cvGetSize(frame), 8, 1 );
            mask = cvCreateImage( cvGetSize(frame), 8, 1 );
            backproject = cvCreateImage( cvGetSize(frame), 8, 1 );
            hist = cvCreateHist( 1, &hdims, CV_HIST_ARRAY, &hranges, 1 );  // 计算直方图
            histimg = cvCreateImage( cvSize(320,200), 8, 3 );
            cvZero( histimg );
        }

        cvCopy( frame, image, 0 );
        cvCvtColor( image, hsv, CV_BGR2HSV );  // 彩色空间转换从 BGR to HSV

        if( track_object ){

            int _vmin = vmin, _vmax = vmax;

            cvInRangeS( hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0),
                        cvScalar(180,256,MAX(_vmin,_vmax),0), mask );  // 得到二值的掩码
            cvSplit( hsv, hue, 0, 0, 0 );  // ?只提取hue色调分量

            if( track_object < 0 ){

                float max_val = 0.f;
                cvSetImageROI( hue, selection );  // 将选择区域设置为ROI
                cvSetImageROI( mask, selection ); // 将选择区域设置为ROI
                cvCalcHist( &hue, hist, 0, mask ); // 计算直方图
                cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 );  // 只找最大值
                // 缩放bin到区间 [0,255]
                cvConvertScale( hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0 );

                cvResetImageROI( hue );  // 移除ROI
                cvResetImageROI( mask );
                track_window = selection;
                track_object = 1;

                cvZero( histimg );
                bin_w = histimg->width / hdims;  // hdims: 直方柱的个数 bin_w:柱的宽度

                // 画直方图
                for( i = 0; i < hdims; i++ ){

                    int val = cvRound( cvGetReal1D(hist->bins,i)*histimg->height/255 );
                    CvScalar color = hsv2rgb(i*180.f/hdims);
                    cvRectangle( histimg, cvPoint(i*bin_w,histimg->height),
                                 cvPoint((i+1)*bin_w,histimg->height - val),
                                 color, -1, 8, 0 );
                }
            }

            cvCalcBackProject( &hue, backproject, hist );
            cvAnd( backproject, mask, backproject, 0 );

            // 调用Camshift算法模块
            cvCamShift( backproject, track_window,
                        cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
                        &track_comp, &track_box );
            track_window = track_comp.rect;

            if( backproject_mode )
                cvCvtColor( backproject, image, CV_GRAY2BGR ); // 使用backproject灰度图像
            if( image->origin )
                track_box.angle = -track_box.angle;
            cvEllipseBox( image, track_box, CV_RGB(255,0,0), 3, CV_AA, 0 );
        }

        if( select_object && selection.width > 0 && selection.height > 0 ){

            cvSetImageROI( image, selection );
            cvXorS( image, cvScalarAll(255), image, 0 );
            cvResetImageROI( image );
        }

        cvShowImage( "CamShiftDemo", image );
        cvShowImage( "Histogram", histimg );

        c = cvWaitKey(10);
        if( c == 27 )
            break;  // ESC退出循环
        switch( c ){

        case 'b':
            backproject_mode ^= 1;
            break;
        case 'c':
            track_object = 0;
            cvZero( histimg );
            break;
        case 'h':
            show_hist ^= 1;
            if( !show_hist )
                cvDestroyWindow( "Histogram" );
            else
                cvNamedWindow( "Histogram", 1 );
            break;
        default:
            ;
        }
    }

    cvReleaseCapture( &capture );
    cvDestroyWindow("CamShiftDemo");

    return 0;
}
</span>

运行结果截图:

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OpenCV:利用Camshift算法进行彩色目标的跟踪

标签:opencv

原文地址:http://blog.csdn.net/u010002704/article/details/43734809

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