OpenCV中取ROI区域RGB的均值，求方差，ROI区域颜色是否明显区分

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#include <iostream>
#include <math.h>

#include <opencv2/opencv.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#define REC_W_H 30
using namespace std;
int main()
{

   IplImage *res, *dst;
   IplImage *dst1, *dst2, *dst3;
   CvRect rect;
   CvRect rect1, rect2, rect3;
   rect.x = 1200, rect.y = 180, rect.width = REC_W_H, rect.height = REC_W_H;//ROI0 的坐标以及大小
   rect1.x = 1200, rect1.y = 240, rect1.width = REC_W_H, rect1.height = REC_W_H;//ROI1 的坐标以及大小
   rect2.x = 1230, rect2.y = 510, rect2.width = REC_W_H, rect2.height = REC_W_H;//ROI2 的坐标以及大小
   rect3.x = 1230, rect3.y = 560, rect3.width = REC_W_H, rect3.height = REC_W_H;//ROI3 的坐标以及大小
   res = cvLoadImage("d:/project/tt/1.bmp");//载入一张图片
   dst = cvCreateImage(cvSize(REC_W_H, REC_W_H), 8, 3);//创建图像空间
   dst1 = cvCreateImage(cvSize(REC_W_H, REC_W_H), 8, 3);//创建图像空间1
   dst2 = cvCreateImage(cvSize(REC_W_H, REC_W_H), 8, 3);//创建图像空间2
   dst3 = cvCreateImage(cvSize(REC_W_H, REC_W_H), 8, 3);//创建图像空间3
   //创建窗口
   cvNamedWindow("res", CV_WINDOW_AUTOSIZE);
   cvNamedWindow("dst", CV_WINDOW_AUTOSIZE);
   cvNamedWindow("dst1", CV_WINDOW_AUTOSIZE);
   cvNamedWindow("dst2", CV_WINDOW_AUTOSIZE);
   cvNamedWindow("dst3", CV_WINDOW_AUTOSIZE);

   //设置ROI区域
   cvSetImageROI(res, rect);
   //提取ROI
   cvCopy(res, dst);

   cvSetImageROI(res, rect1);
   cvCopy(res, dst1);

   cvSetImageROI(res, rect2);
   cvCopy(res, dst2);

   cvSetImageROI(res, rect3);
   cvCopy(res, dst3);

   //取消设置
   cvResetImageROI(res);

   //显示图像
   cvShowImage("res", res);
   cvShowImage("dst", dst);

   cvShowImage("dst1", dst1);
   cvShowImage("dst2", dst2);
   cvShowImage("dst3", dst3);

   //需要提取图像ROI区域RGB的平均值，发现有一个cvAvg函数：
   //CvScalar cvAvg( const CvArr* arr, const CvArr* mask=NULL );
   CvScalar avgChannels = cvAvg(dst);
   double avgB = avgChannels.val[0];
   double avgG = avgChannels.val[1];
   double avgR = avgChannels.val[2];//ROI 的均值

   CvScalar avgChannels1 = cvAvg(dst1);
   double avgB1 = avgChannels1.val[0];
   double avgG1 = avgChannels1.val[1];
   double avgR1 = avgChannels1.val[2];//ROI 1 的均值

   CvScalar avgChannels2 = cvAvg(dst2);
   double avgB2 = avgChannels2.val[0];
   double avgG2 = avgChannels2.val[1];
   double avgR2 = avgChannels2.val[2];//ROI 2 的均值

   CvScalar avgChannels3 = cvAvg(dst3);
   double avgB3 = avgChannels3.val[0];
   double avgG3 = avgChannels3.val[1];
   double avgR3 = avgChannels3.val[2];//ROI 3 的均值

   double ret = sqrt( pow((avgB - avgB2), 2) + pow((avgG - avgG2), 2) + pow((avgR - avgR2), 2));
   double ret1 = sqrt(pow((avgB1 - avgB2), 2) + pow((avgG1 - avgG2), 2) + pow((avgR1 - avgR2), 2));
   double ret2 = sqrt(pow((avgB - avgB3), 2) + pow((avgG - avgG3), 2) + pow((avgR - avgR3), 2));
   double ret3 = sqrt(pow((avgB1 - avgB3), 2) + pow((avgG1 - avgG3), 2) + pow((avgR1 - avgR3), 2));

   cout << "result :" << ret << endl;
   cout << "result1 :" << ret1 << endl;
   cout << "result2 :" << ret2 << endl;
   cout << "result3 :" << ret3 << endl;//控制台打印方差值

   //CV_BGR2HSV();

   cvWaitKey(0);

   cvDestroyWindow("res");
   cvDestroyWindow("dst");

   cvDestroyWindow("dst1");
   cvDestroyWindow("dst2");
   cvDestroyWindow("dst3");

   cvReleaseImage(&res);
   cvReleaseImage(&dst);

   cvReleaseImage(&dst1);
   cvReleaseImage(&dst2);
   cvReleaseImage(&dst3);

   return 0;

}

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