opencv3/C++ 直方图反向投影实例

void calcBackProject( 
const Mat* images, //源数组/图像；有相同的大小和深度(CV_8U或CV_32F)。
int nimages,//源图像的数量
const int* channels, //计算反投影的通道列表；通道数量必须与直方图维度相匹配。
InputArray hist,//输入直方图。
OutputArray backProject, //目标反向投影数组，与images[0]大小、深度相同的单通道数组。
const float** ranges,//每个维度的直方图bin边界数组。
double scale = 1, //输出反向投影的可选比例因子。
bool uniform = true //直方图是否均匀的标志。
);

#include<opencv2/opencv.hpp>
using namespace cv;

Mat hue;
int bins = 10;
void histBackprojection(int, void*);
int main()
{
 Mat src, hsv;
 src = imread("E:/image/image/shape.jpg");
 if (src.empty())
 {
  printf("can not load image \n");
  return -1;
 }
 namedWindow("input", WINDOW_AUTOSIZE); 
 imshow("input", src);
 cvtColor(src, hsv, COLOR_BGR2HSV); 
 hue.create(hsv.size(), hsv.depth());
 int ch[] = {0, 0};
 //分离Hue通道:   相通道
 mixChannels(&hsv, 1, &hue, 1, ch, 1);
 //创建Trackbar来输入bin的数目
 createTrackbar("bins:", "input", &bins, 255, histBackprojection);
 histBackprojection(0, 0);
 waitKey(0);
 return 0;
}

void histBackprojection(int, void*)
{
 MatND hist, backproj;
 int histSize = max(bins, 2);
 float range[] = {0, 255};
 const float *ranges = {range};
 //计算直方图
 calcHist(&hue, 1, 0, Mat(), hist,1, &histSize, &ranges, true, false);
 //将直方图bin的数值归一化到0-255
 normalize(hist, hist, 0, 255, NORM_MINMAX, -1, Mat());
 //计算反向投影
 calcBackProject(&hue, 1, 0, hist, backproj, &ranges, 1, true);
 namedWindow("backprogection", WINDOW_AUTOSIZE);
 imshow("backprogection", backproj);
 //显示直方图
 int binsW = cvRound((double)500/histSize);
 Mat histImg = Mat::zeros(500, 500, CV_8UC3);
 RNG rng(123);
 for (int i = 0; i < bins; i++)
 {
  Scalar color = Scalar(rng.uniform(0,255),rng.uniform(0,255),rng.uniform(0,255));
  rectangle(histImg, Point(i*binsW, 500), Point((i+1)*binsW, 500 - cvRound(hist.at<float>(i) * 500 / 255.0)), color, -1);
 }
 namedWindow("histogram", WINDOW_AUTOSIZE);
 imshow("histogram", histImg);
}