181 lines
4.2 KiB
Markdown
181 lines
4.2 KiB
Markdown
---
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title: opencv应用-基础操作
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categories:
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- 技术
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series: opencv
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tags:
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- opencv
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abbrlink: e8f95ead
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summary: >-
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这篇文章介绍了使用C++和OpenCV库进行图像处理的基础操作，包括图片的读取与展示、像素的读取与修改、图像的基本变换（缩放、旋转、平移、翻转）、以及图像通道的分离与合并。文章详细讲解了每个操作的代码实现，并展示了如何通过OpenCV库提供的函数来完成这些任务。这对于初学者来说是非常有用的，因为它帮助他们理解如何使用OpenCV进行图像处理。
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date: 2026-03-15 09:56:51
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---
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这里用C++进行编程，发现菜鸟教程只有python的版本，那就记录一下。
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# 图片读取与展示
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```cpp
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// 读取图像
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#include<opencv2/opencv.hpp>
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#include<iostream>
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using namespace std;
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using namespace cv;
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int main(){
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Mat src = imread("../img/1.png");
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imshow("input",src);
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waitKey(0);
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destroyAllWindows();
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return 0;
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}
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```
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# 图像基本操作
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## 读取像素
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需要用到三维向量数组Vect3b，这里需要注意的是，Opencv是BGR而不是我们常用的RGB。
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```cpp
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// 读取像素
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#include<opencv2/opencv.hpp>
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#include<iostream>
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using namespace std;
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using namespace cv;
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int main()
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{
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string image_path = "../img/1.png";
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Mat image = imread(image_path);
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if (image.empty()) {
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cout << "错误：无法加载图像，请检查路径是否正确。" << endl;
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return -1;
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}
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Vec3b pixel_value = image.at<Vec3b>(100, 150);
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cout << "B: " << (int)pixel_value[0] << " "
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<< "G: " << (int)pixel_value[1] << " "
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<< "R: " << (int)pixel_value[2] << endl;
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}
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```
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## 修改像素
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```cpp
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// 修改像素
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#include<opencv2/opencv.hpp>
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#include<iostream>
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using namespace std;
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using namespace cv;
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int main()
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{
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string image_path = "../img/1.png";
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Mat image = imread(image_path);
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Mat result = image.clone();
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if (image.empty()) {
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cout << "错误：无法加载图像，请检查路径是否正确。" << endl;
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return -1;
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}
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Rect roi_rect(0, 0, 100, 100);
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Mat roi = result(roi_rect);
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roi.setTo(Scalar(0, 255, 0));
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imshow("Original (Unchanged)", image);
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imshow("Modified Copy", result);
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waitKey(0);
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return 0;
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}
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```
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```cpp
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#include <opencv2/opencv.hpp>
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#include <iostream>
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int main() {
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// 读取图像
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cv::Mat img = cv::imread("../img/1.png");
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if (img.empty()) {
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std::cout << "无法读取图像" << std::endl;
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return -1;
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}
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// 1. 缩放
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cv::Mat resized_img;
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cv::resize(img, resized_img, cv::Size(200, 200));
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cv::imshow("resized_img", resized_img);
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// 2. 旋转
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cv::Mat rotated_img, M_rot;
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cv::Point2f center(img.cols / 2.0, img.rows / 2.0);
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M_rot = cv::getRotationMatrix2D(center, 45, 1.0);
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cv::warpAffine(img, rotated_img, M_rot, img.size());
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cv::imshow("rotated_img", rotated_img);
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// 3. 平移
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cv::Mat translated_img;
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cv::Mat M_trans = (cv::Mat_<float>(2, 3) << 1, 0, 100, 0, 1, 50);
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cv::warpAffine(img, translated_img, M_trans, img.size());
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cv::imshow("translated_img", translated_img);
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// 4. 翻转
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cv::Mat flipped_img;
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cv::flip(img, flipped_img, 1);
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cv::imshow("flipped", flipped_img);
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// 显示结果
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cv::imshow("Original", img);
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cv::waitKey(0);
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return 0;
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}
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```
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```cpp
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// 图像通道分离与合并
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#include<opencv2/opencv.hpp>
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#include<iostream>
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using namespace std;
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using namespace cv;
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int main()
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{
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string image_path = "../img/1.png";
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Mat image = imread(image_path);
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Mat result = image.clone();
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// 定义向量数组接收通道
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vector<Mat> channels;
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// 拆分
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split(result,channels);
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Mat b = channels[0];
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Mat g = channels[1];
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Mat r = channels[2];
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imshow("Blue Channel (Grayscale)", channels[0]);
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imshow("Green Channel (Grayscale)", channels[1]);
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imshow("Red Channel (Grayscale)", channels[2]);
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// merge
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Mat merged_img;
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vector<cv::Mat> channels_to_merge;
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channels_to_merge.push_back(b);
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channels_to_merge.push_back(g);
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channels_to_merge.push_back(r);
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merge(channels_to_merge, merged_img);
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imshow("merged",merged_img);
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waitKey(0);
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return(0);
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}
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``` |