获得RGB图像三种颜色分量并进行条件筛选

#include "highgui.h"
#include"cv.h"

using namespace std;
using namespace cv;

int main(int argc, char *argv[])
{
IplImage *img = cvLoadImage("D:\\huo.jpg");

//R、S、B的阈值Rt,St,Bt
int Rt = 125;
int St = 55;
int Bt = 9;

//获得BGR三种颜色分量
//IplImage* img1 = cvCreateImage(cvSize(640, 480), IPL_DEPTH_8U, 1);
//IplImage* img1 = cvCreateImage(cvSize(640, 480), IPL_DEPTH_8U, 3);
uchar* data = (uchar *)img->imageData;

int step = img->widthStep / sizeof(uchar);
int channels = img->nChannels;
uchar *b_BGR = new uchar[307200], *g_BGR = new uchar[307200], *r_BGR = new uchar[307200];
for (int i = 0; i<img->height; i++)
for (int j = 0; j<img->width; j++)
{
*b_BGR = data[i*step + j*channels + 0];
*g_BGR = data[i*step + j*channels + 1];
*r_BGR = data[i*step + j*channels + 2];
if (*r_BGR < 200)
{
data[i*step + j*channels + 0] = 0;
data[i*step + j*channels + 1] = 0;
data[i*step + j*channels + 2] = 0;
}
else
{
data[i*step + j*channels + 0] = 255;
data[i*step + j*channels + 1] = 255;
data[i*step + j*channels + 2] = 255;
}

}
cvShowImage("img", img);
cvWaitKey(0);
return 0;
}

注意：

1：uchar是一种无符号整型数据，所以可以直接用数字进行对比筛选

2：data[i*step + j*channels + 0]     //BRG三色分量相应位置的颜色数据

3：二值化一定要把三个通道的数据都设为0或255，否则其他两个通道的值不会发生变化

图1：原图（带有火焰的图像）

图2：对火焰R分量进行筛选之后的图像