This project is a C++ application for performing various operations on RGB images. The application utilizes the OpenCV library to perform image processing tasks.

The architecture of this project follows an object-oriented design where the CommonProcesses class serves as the base class, and the Detection class is derived from it. Both LineDetection and CornerDetection classes further inherit from the Detection class. This architecture allows for a modular and extensible design, where common image processing functionalities are defined in the CommonProcesses class, while specific detection tasks like edge and corner detection are implemented in the derived classes.

• Image Loading and Display: Load and visualize images using the CommonProcesses class.
• Conversion to Grayscale: Convert images to grayscale using the RGB2Gray method.
• Noise Reduction: Reduce noise in images using the reduceNoise method.
• Image Rescaling: Rescale images to desired dimensions using the rescaleImage method.
• Histogram Visualization: Visualize the histogram of images using the visualizeHistogram method.
• Edge Detection: Detect edges in images using the LineDetection class.
• Corner Detection: Detect corners in images using the CornerDetection class.
• Mathematical Operations: Perform basic mathematical operations (+, -, *, /) on images using the CommonProcesses class.

1. Image Processing:

   #include "CommonProcesses.h"
   #include <opencv2/opencv.hpp>
   using namespace cv;
   using namespace std;
   
   int main() {
       string path = "./sample.jpg";
       CommonProcesses cp("Sample", path);
       
       // Load and display the image
       cp.showImage();
       
       // Convert to grayscale and display
       cp.RGB2Gray().showImage();
       
       // Reduce noise and display
       cp.reduceNoise().showImage();
       
       // Rescale the image and display
       cp.rescaleImage(500, 100).showImage();
       
       // Compute histogram and visualize
       cp.visualizeHistogram();
       
       return 0;
   }

2. Edge Detection:

   #include "LineDetection.h"
   #include <opencv2/opencv.hpp>
   using namespace cv;
   using namespace std;
   
   int main() {
       string path = "./sample.jpg";
       LineDetection ld("LineDetector", path);
       
       // Detect edges and visualize
       ld.findLine();
       ld.visualizeFeatures();
       
       // Add edges to the image
       ld.putFeature();
       
       // Write edges to a file
       ld.writeFeatures();
       
       // Visualize edges and adjust threshold value
       ld.visualizeFeatures_withTreackbar();
       
       return 0;
   }

3. Corner Detection:

   #include "CornerDetection.h"
   #include <opencv2/opencv.hpp>
   using namespace cv;
   using namespace std;
   
   int main() {
       string path = "./sample.jpg";
       CornerDetection cd("CornerDetector", path);
       
       // Detect corners and visualize
       cd.findCorners();
       cd.visualizeFeatures();
       
       // Add corners to the image
       cd.putFeature();
       
       // Write corners to a file
       cd.writeFeatures();
       
       // Visualize corners and adjust threshold value
       cd.visualizeFeatures_withTreackbar();
       
       return 0;
   }

Line detection is performed using the Hough Line Transform. The LineDetection class extends the Detection class and utilizes OpenCV's HoughLinesP function to detect lines in the image. After detecting the lines, the class provides methods to visualize the detected lines, adjust the threshold value for line detection, and write the detected lines to a file.

Corner detection is performed using the Harris Corner Detection algorithm. The CornerDetection class extends the Detection class and utilizes OpenCV's cornerHarris function to detect corners in the image. After detecting the corners, the class provides methods to visualize the detected corners, adjust the threshold value for corner detection, and write the detected corners to a file.

• C++ compiler
• OpenCV library
• Python3 for matplotlib.h code The code for matplotlib.h has not been written by me, but it is a pre-existing library code.

This project is licensed under the MIT License - see the LICENSE file for details.