C++OpenCV——标记图中三个通道像素值特定区域并输出所占比率

1.需求一 

用红色Mask出一个图片中RGB三个通道像素值都符合在某一个范围内图像区域，用蓝色mask出既符合三通道，像素值在一个范围内也符合亮度在一个区间内的局部区域,并输出符合区域所占整个区域的比例
 

Mat QuickDemo::mask_localImage(Mat& image)
{
	// 输入图像image是单通道的灰度图
	float h = image.rows;
	float w = image.cols;
	int dims = image.channels();

	// 将单通道灰度图转换成为伪灰度图的三通道图像
	Mat image_bgr1;
	cvtColor(image, image_bgr1, COLOR_GRAY2BGR);
	int r_count = 0;

	for (int row = 0; row < h; row++)
	{
		for (int col = 0; col < w; col++) 
		{
			if (image_bgr1.at<Vec3b>(row, col)[0] > 10 && 
				image_bgr1.at<Vec3b>(row, col)[1] > 100 && 
				image_bgr1.at<Vec3b>(row, col)[2]>150)
			{
				image_bgr1.at<Vec3b>(row, col)[0] = 0;
				image_bgr1.at<Vec3b>(row, col)[1] = 0;
				image_bgr1.at<Vec3b>(row, col)[2] = 255;
				r_count++;

			}
			else if (image.at<uchar>(row,col)>50 && 
				image.at<uchar>(row, col)<100)
			{
				image_bgr1.at<Vec3b>(row, col)[0] = 0;
				image_bgr1.at<Vec3b>(row, col)[1] = 255;
				image_bgr1.at<Vec3b>(row, col)[2] = 0;
			}
			else if (image_bgr1.at<Vec3b>(row, col)[0] > 10 && 
				image_bgr1.at<Vec3b>(row, col)[1] > 100 && 
				image_bgr1.at<Vec3b>(row, col)[2] > 150
				&& image.at<uchar>(row, col) > 50 ||
				image.at<uchar>(row, col) < 100)
			{
				image_bgr1.at<Vec3b>(row, col)[0] = 255;
				image_bgr1.at<Vec3b>(row, col)[1] = 0;
				image_bgr1.at<Vec3b>(row, col)[2] = 0;
			}
			
		}
		
	}
	cout << "红色区域的像素个数" << r_count << endl;
	cout << "红色区域的像素所占的比率是：" << r_count / (h * w) << endl;
	return image_bgr1;
}

测试代码：

#include<opencv2/opencv.hpp>
#include<iostream>
#include<quickopencv.h>
using namespace cv;
using namespace std;

int main(int argc, char** argv) {
	Mat src = imread("D:\\testImage\\4.BMP");
	Mat pt = src;
	if (src.empty()) {
		printf("could not load image...");
		return -1;
	}
	namedWindow("原图", WINDOW_FREERATIO);
	imshow("原图", src);
	Mat image_gray;
	cvtColor(src, image_gray, COLOR_BGR2GRAY);

	Mat image_bgr;
	cvtColor(image_gray, image_bgr, COLOR_GRAY2BGR);

	namedWindow("输入窗口", WINDOW_FREERATIO);
	imshow("输入窗口", image_bgr);

	int gray_dims = image_gray.channels();
	int bgr_dims = image_bgr.channels();

	cout << "image_gray的通道数：" << gray_dims << endl;
	cout << "image_bgr的通道数：" << bgr_dims << endl;
	QuickDemo qd;

	Mat new_image = qd.mask_localImage(image_gray);
	namedWindow("new_image", WINDOW_FREERATIO);
	imshow("new_image", new_image);
	waitKey(0);
	return 0;
}

           

 原图和灰度图

 标记图

其他颜色区域所占的比率大家有兴趣可以自己输出 

需求二

我们需要对ROI（感兴趣的区域）框起来。

void QuickDemo::draw_interest_pluse(Mat& image, int re_h, int re_w) {
	// 首先打上掩膜
	Mat image_add = mask_localImage(image);
	int h = image_add.rows; // 原图高
	int w = image_add.cols; // 原图宽
	int r_h = h / re_h; // 分割高度以后的区域
	int r_w = w / re_w; // 分割宽度以后的区域
	// vector<Point> points; // 设置容器，用来存储坐标
	for (int i = 0; i < re_h; i++) {
		for (int j = 0; j < re_w; j++) {
			vector<Point> points; // 设置容器，用来存储坐标
			for (int row = i * r_h; row < r_h * (i + 1); row++) {
				for (int col = j * r_w; col < (j + 1) * r_w; col++) {
					if (image_add.at<Vec3b>(row, col)[0] == 0 &&
						image_add.at<Vec3b>(row, col)[1] == 0 &&
						image_add.at<Vec3b>(row, col)[2] == 255) {
						// 查找符合要求的像素点
						Point midPoint;
						midPoint.x = col;
						midPoint.y = row;
						points.push_back(midPoint);
					}
				}
			}
			Rect rect = boundingRect(points);
			rectangle(image_add, rect, Scalar(0, 0, 0), 1, 8);
		}
	}
	namedWindow("add_mask", WINDOW_FREERATIO);
	imshow("add_mask", image_add);
}

测试函数如下：

#include<opencv2/opencv.hpp>
#include<iostream>
#include<quickopencv.h>
using namespace cv;
using namespace std;


int main(int argc, char** argv) {
	Mat src = imread("D:\\testImage\\123.BMP");
	if (src.empty()) {
		printf("could not load image...");
		return -1;
	}

	Mat src_gray;
	cvtColor(src, src_gray, COLOR_BGR2GRAY);

	QuickDemo qd;
	Mat after_image = qd.mask_localImage(src_gray);
	namedWindow("new_image", WINDOW_FREERATIO);
	imshow("new_image", after_image);

	 qd.draw_interest_pluse(src_gray, 2, 4);
	waitKey(0);
	return 0;
}

结果如下：

上图是根据需求一实现的对ROI区域进行掩模的图，我们需要对他进行框起来

结果如下：