图像阈值程序

阈值测试程序，读取相邻两张图片，将其转为HSV后，采用inrange阈值函数进行二值化，最后统计白色像素点的个数。或者直接RGB通道进行阈值分割。

//
#include "stdafx.h"
#include "opencv2/opencv.hpp"  
#include     
#include
#include 
#include   
#include   
#include 
#include
#include

#include 
#include 
// for fileoutput
#include 
#include 

using namespace cv;
using namespace std;

int bSums(Mat src)
{

	int counter = 0;
	//迭代器访问像素点
	Mat_::iterator it = src.begin();
	Mat_::iterator itend = src.end();
	for (; it != itend; ++it)
	{
		if ((*it) > 0) counter += 1;//二值化后，像素点是0或者255
	}
	return counter;
}

//
Mat frame, frame1, imgThresholded, hsv, diff;  //定义矩阵


int main(int argc, char** argv)
{

	frame = imread("G:\研三资料\2021.10月汇报\阈值测试\vs\云彩图\8.jpg");
	frame1 = imread("G:\研三资料\2021.10月汇报\阈值测试\vs\云彩图\8_1.jpg");
	absdiff(frame, frame1, diff);
	imshow("frame1", diff);
	imwrite("G:\研三资料\2021.10月汇报\阈值测试\vs\云彩图\8_81diff.jpg", diff);
	cvtColor(diff, hsv, CV_BGR2HSV);
	imshow("frame0", hsv);
	imwrite("G:\研三资料\2021.10月汇报\阈值测试\vs\云彩图\8_81hsv.jpg", hsv);
	//threshold(hsv,imgThresholded,95,255,1);
	inRange(hsv, Scalar(70, 70, 46), Scalar(180, 180, 180), imgThresholded);
	imshow("frame", imgThresholded);
	imwrite("G:\研三资料\2021.10月汇报\阈值测试\vs\云彩图\8_81erzhi.jpg", imgThresholded);
	int a = bSums(imgThresholded);//调用函数bSums
	cout << "A:" << a;
	waitKey(0);
	return 0;
}