C++ OpenCV Basic Operations

Basic Image Operations

Read, Display, and Save Images

In OpenCV, the basic operations on images include reading, displaying, and saving images. These operations are the foundation of image processing.

Reading Images: Use theimreadfunction to read an image. The first parameter of this function is the path of the image file, and the second parameter is the way to read the image (such as color image, grayscale image, etc.).

cv::Mat image = cv::imread("image.jpg", cv::IMREAD_COLOR);

Displaying Images: Use theimshowfunction to display an image. The first parameter of this function is the name of the window, and the second parameter is the image to be displayed.

cv::imshow("Display Window", image);
cv::waitKey(0); // 等待按键按下
Saving Images: Use theimwritefunction to save an image. The first parameter of this function is the path of the file to save, and the second parameter is the image to be saved. 
cv::imwrite("output.jpg", image);

Basic Properties of Images

The basic properties of an image include size, number of channels, and pixel values.

Size: The size of an image can be obtained through therowsandcolsattribute.

int height = image.rows;
int width = image.cols;

Number of Channels: The number of channels of an image can be obtained through thechannels()method.

int channels = image.channels();

Pixel Values: can be accessed through theatmethod to access the pixel values of an image.

cv::Vec3b pixel = image.at<cv::Vec3b>(y, x); // 访问(x, y)处的像素值

Creation and Initialization of Images

You can use theMatclass to create and initialize images.

Creating Images: You can create an image of a specified size and type.

cv::Mat newImage(480, 640, CV_8UC3, cv::Scalar(0, 0, 255)); // 创建一个640x480的红色图像

Initializing Images: Use thesetTomethod to initialize an image.

image.setTo(cv::Scalar(255, 255, 255)); // 将图像初始化为白色

Pixel Operations on Images

Pixel operations on an image include iterating over pixels and modifying pixel values.

Iterating Over Pixels: You can use a double loop to iterate over every pixel of the image.

for (int y = 0; y < image.rows; y++) {
    for (int x = 0; x < image.cols; x++) {
        cv::Vec3b& pixel = image.at<cv::Vec3b>(y, x);
        // 对像素进行操作
    }
}

Modifying Pixel Values: You can directly modify the value of a pixel.

pixel[0] = 255; // 将蓝色通道设置为255
pixel[1] = 0;   // 将绿色通道设置为0
pixel[2] = 0;   // 将红色通道设置为0

Geometric Transformations of Images

Scaling, Rotation, Translation, and Flipping

Geometric transformations of an image include scaling, rotation, translation, and flipping.

Scaling: Use theresizefunction to scale an image.

cv::Mat resizedImage;
cv::resize(image, resizedImage, cv::Size(newWidth, newHeight));

Rotation: Use thegetRotationMatrix2DandwarpAffinefunction to rotate an image.

cv::Point2f center(image.cols / 2.0, image.rows / 2.0);
cv::Mat rotationMatrix = cv::getRotationMatrix2D(center, angle, 1.0);
cv::Mat rotatedImage;
cv::warpAffine(image, rotatedImage, rotationMatrix, image.size());

Translation: Use thewarpAffinefunction to translate an image.

cv::Mat translationMatrix = (cv::Mat_<double>(2, 3) << 1, 0, tx, 0, 1, ty);
cv::Mat translatedImage;
cv::warpAffine(image, translatedImage, translationMatrix, image.size());

Flipping: Use theflipfunction to flip an image.

cv::Mat flippedImage;
cv::flip(image, flippedImage, 1); // 1表示水平翻转，0表示垂直翻转

Affine Transformation and Perspective Transformation

Affine Transformation: Affine transformation is a linear transformation plus translation, and can be implemented using thewarpAffinefunction.

cv::Mat affineMatrix = cv::getAffineTransform(srcPoints, dstPoints);
cv::Mat affineImage;
cv::warpAffine(image, affineImage, affineMatrix, image.size());

Perspective Transformation: Perspective transformation is a more general transformation, and can be implemented using thewarpPerspectivefunction.

cv::Mat perspectiveMatrix = cv::getPerspectiveTransform(srcPoints, dstPoints);
cv::Mat perspectiveImage;
cv::warpPerspective(image, perspectiveImage, perspectiveMatrix, image.size());

Color Space Conversion of Images

Color spaces such as RGB, grayscale, and HSV

The color spaces of an image include RGB, grayscale, HSV, etc.

  • RGB: RGB is the most common color space, representing three channels: red, green, and blue.
  • Grayscale: A grayscale image has only one channel, which represents brightness.
  • HSV: HSV color space represents Hue, Saturation, and Value.

Color Space Conversion

Use thecvtColorfunction to perform color space conversion.

RGB to Grayscale：

cv::Mat grayImage;
cv::cvtColor(image, grayImage, cv::COLOR_BGR2GRAY);

RGB to HSV：

cv::Mat hsvImage;
cv::cvtColor(image, hsvImage, cv::COLOR_BGR2HSV);

Channel Separation and Merging

Channel Separation: Use thesplitfunction to separate the channels of an image.

std::vector<cv::Mat> channels;
cv::split(image, channels);

Channel Merging: Use themergefunction to merge multiple channels into one image.

cv::Mat mergedImage;
cv::merge(channels, mergedImage);

Examples

The basic operations of C++ OpenCV include image reading, displaying, saving, pixel operations, obtaining image properties, etc.

The following are some common OpenCV basic operations and their code examples:

1. Reading and Displaying Images

Example

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

using namespace cv;
using namespace std;

int main() {
    // Read image
    Mat image = imread("test.jpg");

    // Check whether the image was loaded successfully
    if (image.empty()) {
        cout << "Error: Failed to load image, please check whether the path is correct." << endl;
        return -1;
    }

    // Display image
    namedWindow("Display Image", WINDOW_AUTOSIZE);
    imshow("Display Image", image);

    // Wait for a key press
    waitKey(0);

    // Close the window
    destroyAllWindows();

    return 0;
}

2. Saving Images

Example

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

using namespace cv;
using namespace std;

int main() {
    // Read image
    Mat image = imread("test.jpg");

    if (image.empty()) {
        cout << "Error: Failed to load image, please check whether the path is correct." << endl;
        return -1;
    }

    // Save image
    bool isSaved = imwrite("saved_image.jpg", image);
    if (isSaved) {
        cout << "Image saved successfully!" << endl;
    } else {
        cout << "Failed to save image!" << endl;
    }

    return 0;
}

3. Obtaining Image Properties

Example

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

using namespace cv;
using namespace std;

int main() {
    // Read image
    Mat image = imread("test.jpg");

    if (image.empty()) {
        cout << "Error: Failed to load image, please check whether the path is correct." << endl;
        return -1;
    }

    // Get image properties
    int width = image.cols;  // Image width
    int height = image.rows; // Image height
    int channels = image.channels(); // Number of image channels

    cout << "Image width: " << width << endl;
    cout << "Image height: " << height << endl;
    cout << "Number of image channels: " << channels << endl;

    return 0;
}

4. Accessing and Modifying Pixel Values

Example

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

using namespace cv;
using namespace std;

int main() {
    // Read image
    Mat image = imread("test.jpg");

    if (image.empty()) {
        cout << "Error: Failed to load image, please check whether the path is correct." << endl;
        return -1;
    }

    // Access pixel values (BGR format)
    Vec3b pixel = image.at<Vec3b>(100, 100); // Get the pixel value at position (100, 100)
    cout << "B: " << (int)pixel[0] << ", G: " << (int)pixel[1] << ", R: " << (int)pixel[2] << endl;

    // Modify pixel value
    image.at<Vec3b>(100, 100) = Vec3b(255, 0, 0); // Set the pixel at position (100, 100) to blue

    // Display the modified image
    imshow("Modified Image", image);
    waitKey(0);
    destroyAllWindows();

    return 0;
}

5. Image Color Space Conversion

Example

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

using namespace cv;
using namespace std;

int main() {
    // Read image
    Mat image = imread("test.jpg");

    if (image.empty()) {
        cout << "Error: Failed to load image, please check whether the path is correct." << endl;
        return -1;
    }

    // Convert to grayscale image
    Mat grayImage;
    cvtColor(image, grayImage, COLOR_BGR2GRAY);

    // Display the grayscale image
    imshow("Gray Image", grayImage);
    waitKey(0);
    destroyAllWindows();

    return 0;
}

6. Cropping and Scaling Images

Example

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

using namespace cv;
using namespace std;

int main() {
    // Read image
    Mat image = imread("test.jpg");

    if (image.empty()) {
        cout << "Error: Failed to load image, please check whether the path is correct." << endl;
        return -1;
    }

    // Crop image
    Rect roi(100, 100, 200, 200); // (x, y, width, height)
    Mat croppedImage = image(roi);

    // Scale image
    Mat resizedImage;
    resize(image, resizedImage, Size(400, 400)); // Scale to 400x400

    // Display the cropped and scaled image
    imshow("Cropped Image", croppedImage);
    imshow("Resized Image", resizedImage);
    waitKey(0);
    destroyAllWindows();

    return 0;
}

7. Copying and Cloning Images

Example

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

using namespace cv;
using namespace std;

int main() {
    // Read image
    Mat image = imread("test.jpg");

    if (image.empty()) {
        cout << "Error: Failed to load image, please check whether the path is correct." << endl;
        return -1;
    }

    // Copy image
    Mat copiedImage = image.clone();

    // Modify the copied image
    circle(copiedImage, Point(100, 100), 50, Scalar(0, 255, 0), 2); // Draw a circle on the copied image

    // Display the original image and the modified image
    imshow("Original Image", image);
    imshow("Copied Image", copiedImage);
    waitKey(0);
    destroyAllWindows();

    return 0;
}

8. Geometric Transformations of Images

Example

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

using namespace cv;
using namespace std;

int main() {
    // Read image
    Mat image = imread("test.jpg");

    if (image.empty()) {
        cout << "Error: Failed to load image, please check whether the path is correct." << endl;
        return -1;
    }

    // Rotate image
    Mat rotatedImage;
    Point2f center(image.cols / 2, image.rows / 2); // Rotation center
    double angle = 45; // Rotation angle
    double scale = 1.0; // Scale ratio
    Mat rotationMatrix = getRotationMatrix2D(center, angle, scale);
    warpAffine(image, rotatedImage, rotationMatrix, image.size());

    // Display the rotated image
    imshow("Rotated Image", rotatedImage);
    waitKey(0);
    destroyAllWindows();

    return 0;
}
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