Can someone answer my C++ OpenCV q?

Programming
,
1

This code aims to binarize an image, detect the blobs in the image, label the regions of interest (ROI), and draw a rectangle around the ROI.

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

#define IMAGE_PATH "test2.bmp"
#define COLOR_IMAGE_WINDOW_NAME "color image"
#define GRAY_IMAGE_WINDOW_NAME "gray image"

using namespace cv;
using namespace std;

int main()
{
    Mat src = imread("test1.bmp", IMREAD_GRAYSCALE);
    Mat binary;
    threshold(src, binary, 128, 255, THRESH_BINARY);

    vector<KeyPoint> keypoints;
    SimpleBlobDetector::Params params;
    params.filterByArea = true;
    params.minArea = 100;
    params.maxArea = 10000;
    params.filterByCircularity = true;
    params.minCircularity = 0.1;
    params.filterByConvexity = true;
    params.minConvexity = 0.87;
    params.filterByInertia = true;
    params.minInertiaRatio = 0.01;

    Ptr<SimpleBlobDetector> detector = SimpleBlobDetector::create(params);
    detector->detect(binary, keypoints);

    Mat labeledImage;
    Mat labelStats;
    Mat labelCentroids;

    int nLabels = connectedComponentsWithStats(binary, labeledImage, labelStats, labelCentroids);
    
    Rect roi(10, 10, 100, 100);
    Mat roiImage = src(roi);
    rectangle(src, roi, Scalar(255, 0, 0), 2);
    
    imshow("binary", binary);
    imshow("src", src);

    waitKey(0);

    destroyAllWindows();

    return 0;
}

This code binarizes an image using the threshold() function, detects blobs in the binary image using the SimpleBlobDetector() function, labels regions of interest (ROI) with connectedComponentsWithStats(), and draws a rectangle around the ROI.

2

The code binarizes an image by applying a threshold to it using the threshold() function. It then detects blobs in the binary image using the SimpleBlobDetector() function. The regions of interest (ROI) are labeled using the connectedComponentsWithStats() function. Finally, a rectangle is drawn around the ROI using the rectangle() function.

The code also displays the binary image and the original image using the imshow() function, and waits for a key press using the waitKey() function. The windows are then closed using the destroyAllWindows() function.

Please note that the image path is defined as “test1.bmp” in the code, but the variable src is actually assigned the image “test2.bmp”.