#include<opencv2/opencv.hpp>
#include<iostream>
#include<math.h>

using namespace cv;
using namespace std;

//直方圖反映的是統計的資訊，它反映了影象中畫素值在特定範圍（ranges）內的畫素個數（bin）。
Mat src,hsv;
Mat hue;
int bins = 12;
void creatrackbar(int, void*);

int main(int argc, char** argv)
{
	src = imread("D:/test/hand.png"
 
);
	if (src.empty())
	{
		cout << "圖片未找到" << endl;
		return -1;
	}
	cvtColor(src, hsv, CV_BGR2HSV);
	hue.create(hsv.size(), hsv.depth());
	int nchannels[] = { 0,0 };
	mixChannels(&hsv, 1, &hue, 1, nchannels, 1);

	namedWindow("input image", CV_WINDOW_AUTOSIZE);
	createTrackbar("move"
 
, "input image", &bins, 180, creatrackbar);
	creatrackbar(0, 0);
	imshow("input image", src);
	waitKey(0);
	return 0;
}

void creatrackbar(int, void *)
{
	Mat h_hist;
	float range[] = {0,180};
	const float *histRanges = { range };
	/*----直方圖計算------*/
	calcHist(&hue, 1, 0, Mat(), h_hist, 1, &bins,
 
 &histRanges, true, false);
	//歸一化處理
	normalize(h_hist, h_hist, 0, 255, NORM_MINMAX, -1, Mat());
	Mat backprj;
	//直方圖反向投影
	calcBackProject(&hue, 1, 0, h_hist, backprj, &histRanges, 1, true);
	imshow("backprj", backprj);
	int img_w = 512;
	int img_h = 400;
	int bin_w = img_w / bins;
	Mat imagebackground(img_w, img_h, CV_8UC3, Scalar(0, 0, 0));
	for(int i=1;i<bins;i++)
	{
		rectangle(imagebackground,
			Point((i-1)*bin_w,img_h-cvRound((h_hist.at<float>(i-1))*(400 / 255))),
			Point((i)*bin_w, img_h),Scalar(90,123,213),1,8);
	}
	imshow("imagebackground", imagebackground);
	return;
}

最後執行結果如圖所示：