int main(void)
{
GetHistogram gh;
ObjectFinder of;
cv::Mat img1, img2;
cv::Mat imgROI;
cv::Mat histogram;
cv::Mat backProject;
img1 = cv::imread("..\\..\\..\\source\\1.jpg");
if(!img1.data)
return 0;
imgROI = img1(cv::Rect(80,300,35,40));
cv::rectangle(img1,cv::Rect(110,260,35,40),cv::Scalar(0,0,255));
cv::namedWindow("img1");
cv::imshow("img1", img1);
//获得imgROI的直方图
histogram = gh.getHueHistogram(imgROI, 65);
cv::normalize(histogram,histogram,1.0);
of.setHistogram(histogram);
//获取并处理第二幅图像
cv::Mat hsv;
std::vector<cv::Mat> hue;
img2 = cv::imread("..\\..\\..\\source\\2.jpg");
cv::cvtColor(img2, hsv, CV_BGR2HSV);
cv::split(hsv, hue);
cv::threshold(hue[1], hue[1], 65, 255, cv::THRESH_BINARY);//这个是为了将低饱和度的图像从反向投影结果中剔除
//对于第二幅图进行反向投影，使用第一幅图ROI的直方图
backProject = of.finder(img2);
cv::bitwise_and(backProject, hue[1], backProject);
cv::namedWindow("backProject");
cv::imshow("backProject",backProject);
//均值漂移
cv::Rect rect(110,260,35,40);
cv::rectangle(img2, rect, cv::Scalar(0,0,255));
cv::TermCriteria criteria(cv::TermCriteria::MAX_ITER,10,0.01);//最大迭代次数是10，移动距离阈值是0.01
cv::meanShift(backProject,rect,criteria);
cv::rectangle(img2, rect, cv::Scalar(0,255,0));
cv::namedWindow("img2");
cv::imshow("img2",img2);
cv::waitKey(0);
return 0;
}
