//对运动物体的跟踪：//如果背景固定,可用帧差法 然后在计算下连通域 将面积小的去掉即可//如果背景单一,即你要跟踪的物体颜色和背景色有较大区别 可用基于颜色的跟踪 如CAMSHIFT 鲁棒性都是较好的//如果背景复杂,如背景中有和前景一样的颜色 就需要用到一些具有预测性的算法 如卡尔曼滤波等 可以和CAMSHIFT结合#include "cv.h"#include "highgui.h"#include <stdio.h>#include <ctype.h>IplImage *image = 0, *hsv = 0, *hue = 0, *mask = 0, *backproject = 0, *histimg = 0;//用HSV中的Hue分量进行跟踪CvHistogram *hist = 0;//直方图类int backproject_mode = 0;int select_object = 0;int track_object = 0;int show_hist = 1;CvPoint origin;CvRect selection;CvRect track_window;//CvRect//矩形框的偏移和大小//typedef struct CvRect//{//int x; /* 方形的最左角的x-坐标 *///int y; /* 方形的最上或者最下角的y-坐标 *///int width; /* 宽 *///int height; /* 高 *///}//CvRect;/* 构造函数*///inline CvRect cvRect( int x, int y, int width, int height );CvBox2D track_box; // tracking 返回的区域 box，带角度//typedef struct CvBox2D//{//CvPoint2D32f center; /* 盒子的中心 *///CvSize2D32f size; /* 盒子的长和宽 *///float angle; /* 水平轴与第一个边的夹角，用弧度表示*///}实际上是椭圆的外接矩形，不同于CvRect结构，此矩形可以是倾斜的。画椭圆那个函数也用到这个结构。CvConnectedComp track_comp;//连接部件// typedef struct CvConnectedComp {// double area; /* 连通域的面积 */// float value; /* 分割域的灰度缩放值 */// CvRect rect; /* 分割域的 ROI */// } CvConnectedComp;int hdims = 48;//划分直方图bins的个数，越多越精确float hranges_arr[] = {0,180};//像素值的范围float* hranges = hranges_arr;//用于初始化CvHistogram类int vmin = 10, vmax = 256, smin = 30;//用于设置滑动条//鼠标回调函数,该函数用鼠标进行跟踪目标的选择void on_mouse( int event, int x, int y, int flags,void* param ) //源程序丢失 void* param{ if( !image ) return; if( image->origin ) y = image->height - y; //如果图像原点坐标在左下,则将其改为左上 if( select_object ) //select_object为1,表示在用鼠标进行目标选择 //此时对矩形类selection用当前的鼠标位置进行设置 { selection.x = MIN(x,origin.x); //#define MIN(a,b) ((a) > (b) ? (b) : (a)) selection.y = MIN(y,origin.y); selection.width = selection.x + CV_IABS(x - origin.x); //#define CV_IABS(a) (((a) ^ ((a) < 0 ? -1 : 0)) - ((a) < 0 ? -1 : 0)) 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: //鼠标按下,开始点击选择跟踪物体 origin = cvPoint(x,y); selection = cvRect(x,y,0,0);//CvRect cvRect(int x(左上角), int y(左上角), int width, int height); //Stores coordinates of a rectangle. select_object = 1; break; case CV_EVENT_LBUTTONUP: //鼠标松开,完成选择跟踪物体 select_object = 0; if( selection.width > 0 && selection.height > 0 ) //如果选择物体有效，则打开跟踪功能 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 )//用于将Hue量转换成RGB量{ 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 ); //用于显示直方图 cvNamedWindow( "CamShiftDemo", 1 ); //用于显示视频 cvSetMouseCallback( "CamShiftDemo", on_mouse, NULL ); //设置鼠标回调函数 cvCreateTrackbar( "Vmin", "CamShiftDemo", &vmin, 256, 0 ); cvCreateTrackbar( "Vmax", "CamShiftDemo", &vmax, 256, 0 ); cvCreateTrackbar( "Smin", "CamShiftDemo", &smin, 256, 0 ); //设置滑动条 for(;;) //进入视频帧处理主循环 { int i, bin_w, c; frame = cvQueryFrame( capture ); if( !frame ) break; if( !image ) //image为0,表明刚开始还未对image操作过,先建立一些缓冲区 { /* allocate all the buffers */ 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 ); //分配掩膜图像空间 backproject = cvCreateImage( cvGetSize(frame), 8, 1 ); //分配反向投影图空间,大小一样,单通道 hist = cvCreateHist( 1, &hdims, CV_HIST_ARRAY, &hranges, 1 ); //分配直方图空间// 计算直方图 histimg = cvCreateImage( cvSize(320,200), 8, 3 ); //分配用于直方图显示的空间 cvZero( histimg ); //置背景为黑色 } cvCopy( frame, image, 0 ); cvCvtColor( image, hsv, CV_BGR2HSV ); // 彩色空间转换 BGR to HSV //把图像从RGB表色系转为HSV表色系 if( track_object ) //track_object非零,表示有需要跟踪的物体 { int _vmin = vmin, _vmax = vmax; cvInRangeS( hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0), cvScalar(180,256,MAX(_vmin,_vmax),0), mask ); //CVAPI(void) cvInRangeS( const CvArr* src, CvScalar lower,CvScalar upper, CvArr* dst ); //制作掩膜板，只处理像素值为H：0~180，S：smin~256，V：vmin~vmax之间的部分 //用于检查图像中像素的灰度是否属于某一指定范围。cvInRange()检查，src的每一个像素点是否落在lower和upper范围中。 //如果src的值大于或者等于lower值，并且小于upper值，那么dst中对应的对应值将被设置为0xff；否则，dst的值将被设置为0。 cvSplit( hsv, hue, 0, 0, 0 ); // 只提取 HUE 分量 //Divides a multi-channel array into several single-channel arrays. //void cvSplit(const CvArr* src, CvArr* dst0, CvArr* dst1, CvArr* dst2, CvArr* dst3) if( track_object < 0 ) //如果需要跟踪的物体还没有进行属性提取，则进行选取框类的图像属性提取 { float max_val = 0.f; cvSetImageROI( hue, selection ); // 得到选择区域 for ROI 基于给定的矩形设置图像的ROI（感兴趣区域，region of interesting） //设置原选择框为ROI void cvSetImageROI（IplImage* image，CvRect rect） cvSetImageROI( mask, selection ); // 得到选择区域 for mask //设置掩膜板选择框为ROI cvCalcHist( &hue, hist, 0, mask ); // 计算直方图 //得到选择框内且满足掩膜板内的直方图 cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 ); // 只找最大值 /* Finds indices and values of minimum and maximum histogram bins CVAPI(void) cvGetMinMaxHistValue( const CvHistogram* hist, float* min_value, float* max_value, int* min_idx CV_DEFAULT(NULL), int* max_idx CV_DEFAULT(NULL));*/ cvConvertScale( hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0 ); // 缩放 bin 到区间 [0,255]// 对直方图的数值转为0~255 //Converts one array to another with optional linear transformation. //dst(I) = scalesrc(I) + (shift0; shift1; :::) /*CVAPI(void) cvConvertScale( const CvArr* src, CvArr* dst, double scale CV_DEFAULT(1), double shift CV_DEFAULT(0) );*/ cvResetImageROI( hue ); // remove ROI /* Resets image ROI and COI CVAPI(void) cvResetImageROI( IplImage* image );*/ cvResetImageROI( mask ); //去除ROI track_window = selection; track_object = 1; //置track_object为1,表明属性提取完成 //CvRect track_window; cvZero( histimg ); //histimg = cvCreateImage( cvSize(320,200), 8, 3 ); //分配用于直方图显示的空间 bin_w = histimg->width / hdims; // hdims: 条的个数，则 bin_w 为条的宽度 //int hdims = 48;划分直方图bins的个数，越多越精确 // 画直方图 for( i = 0; i < hdims; i++ ) //画直方图到图像空间 { int val = cvRound( cvGetReal1D(hist->bins,i)*histimg->height/255 ); //int cvRound (double value//对一个double型的数进行四舍五入，并返回一个整型数！ //CVAPI(double) cvGetReal1D( const CvArr* arr, int idx0 ); //Input array. Must have a single channel. //Return a specific element of single-channel 1D, 2D, 3D or nD array. 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 ); //void cvRectangle(CvArr* img, CvPoint pt1, CvPoint pt2, CvScalar color, int thickness=1, //int line-Type=8, int shift=0 ) pt1,pt2为对顶点 } } cvCalcBackProject( &hue, backproject, hist ); //void cvCalcBackProject(IplImage** image, CvArr* backProject, const CvHistogram* hist) //计算hue的反向投影图 cvAnd( backproject, mask, backproject, 0 ); //void cvAnd(const CvArr* src1, const CvArr* src2, CvArr* dst, const CvArr* mask=NULL) //得到掩膜内的反向投影 // calling CAMSHIFT 算法模块 cvCamShift( backproject, track_window, cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ), &track_comp, &track_box ); //CvBox2D track_box;CvRect track_window; ////使用MeanShift算法对backproject中的内容进行搜索,返回跟踪结果 track_window = track_comp.rect;//收敛后搜索窗口的位置 //得到跟踪结果的矩形框 //CvConnectedComp track_comp; //连接部件 // typedef struct CvConnectedComp { // double area; /* 连通域的面积 */ // float value; /* 分割域的灰度缩放值 */ // CvRect rect; /* 分割域的 ROI */ // } CvConnectedComp; if( backproject_mode ) //int backproject_mode = 0; cvCvtColor( backproject, image, CV_GRAY2BGR ); // 使用backproject灰度图像 if( image->origin ) //image->origin = frame->origin; track_box.angle = -track_box.angle; cvEllipseBox( image, track_box, CV_RGB(255,0,0), 3, CV_AA, 0 ); //void cvEllipseBox(CvArr* img, CvBox2D box, CvScalar color, int thickness=1, int lineType=8, int shift=0 ) //画椭圆 //画出跟踪结果的位置 } if( select_object && selection.width > 0 && selection.height > 0 ) //如果正处于物体选择，画出选择框 { cvSetImageROI( image, selection ); cvXorS( image, cvScalarAll(255), image, 0 ); //void cvXorS(const CvArr* src, CvScalar value, CvArr* dst, const CvArr* mask=NULL) //src或value=dst cvResetImageROI( image ); } cvShowImage( "CamShiftDemo", image ); cvShowImage( "Histogram", histimg ); c = cvWaitKey(10); if( c == 27 ) break; // exit from for-loop switch( c ) { case 'b': backproject_mode ^= 1;//^异或操作，0^0=0,0^1=1,1^0=1,1^1=0 break; case 'c': track_object = 0; cvZero( histimg );//直方图清除后，track_object = 0;方便重新取属性 break; case 'h': show_hist ^= 1; if( !show_hist ) cvDestroyWindow( "Histogram" ); else cvNamedWindow( "Histogram", 1 ); break; default: ; } } cvReleaseCapture( &capture ); cvDestroyWindow("CamShiftDemo"); return 0;}
