对RGB三个通道进行操作示例

#include <iostream>
#include <opencv2\opencv.hpp>

using namespace std;
using namespace cv;

int main(int, char *argv[])
{
    
    
	Mat OriginalImg;

	OriginalImg = imread("dst_pic51.jpg", IMREAD_COLOR);//读取原始彩色图像
	if (OriginalImg.empty())  //判断图像对否读取成功
	{
    
    
		cout << "错误!读取图像失败\n";
		return -1;
	}
	//	imshow("原图", OriginalImg); //显示原始图像
	cout << "Width:" << OriginalImg.rows << "\tHeight:" << OriginalImg.cols << endl;//打印长宽

	//Mat ResizeImg;
	//if (OriginalImg.cols > 640)
	//{
    
    
	//	resize(OriginalImg, ResizeImg, Size(640, 640 * OriginalImg.rows / OriginalImg.cols));
	//}
	//imshow("尺寸变换图", ResizeImg);

	unsigned char pixelB, pixelG, pixelR;  //记录各通道值
	unsigned char DifMax = 100;             //基于颜色区分的阈值设置
//	unsigned char B = 138, G = 63, R = 23; //各通道的阈值设定，针对与蓝色车牌
//	unsigned char B = 118, G = 63, R = 23; //各通道的阈值设定，针对与蓝色车牌
	Mat BinRGBImg = OriginalImg.clone();  //二值化之后的图像
	int i = 0, j = 0;
	for (i = 0; i < OriginalImg.rows; i++)   //通过颜色分量将图片进行二值化处理
	{
    
    
		for (j = 0; j < OriginalImg.cols; j++)
		{
    
    
			pixelB = OriginalImg.at<Vec3b>(i, j)[0]; //获取图片各个通道的值
			pixelG = OriginalImg.at<Vec3b>(i, j)[1];
			pixelR = OriginalImg.at<Vec3b>(i, j)[2];

			if (pixelB-130>0)
			{
    
                                               //将各个通道的值和各个通道阈值进行比较
				BinRGBImg.at<Vec3b>(i, j)[0] = 255;     //符合颜色阈值范围内的设置成白色
				BinRGBImg.at<Vec3b>(i, j)[1] = 255;
				BinRGBImg.at<Vec3b>(i, j)[2] = 255;
			}
			else
			{
    
    
				BinRGBImg.at<Vec3b>(i, j)[0] = 0;        //不符合颜色阈值范围内的设置为黑色
				BinRGBImg.at<Vec3b>(i, j)[1] = 0;
				BinRGBImg.at<Vec3b>(i, j)[2] = 0;
			}
		}
	}
	imshow("基于颜色信息二值化", BinRGBImg);        //显示二值化处理之后的图像
	imwrite("BlueI.jpg", BinRGBImg);

	waitKey();
	return 0;

}