OpenCV exercises

Here the histogram equalization algorithm is used with the normalized accumulated histogram to update the pixels intensity. With this algorithm, the pixel with highest intensity is going to assume the value of 255 and the others pixel also change accordingly.

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

using namespace cv;
using namespace std;

int main(int argc, char** argv){
    Mat image, grey;
    int width, height;
    VideoCapture cap;

    int histSize = 256;
    float range[] = {0, 256};
    const float* histRange = {range};
    Mat hist;

    cap.open(0);

    if (!cap.isOpened()){
        cout << "No cameras available" << endl;
        exit(1);
    }

    width  = cap.get(CV_CAP_PROP_FRAME_WIDTH);
    height = cap.get(CV_CAP_PROP_FRAME_HEIGHT);
    
    cout << "###### Image dimensions ######" << endl    
         << "Width = " << width << endl
         << "Height  = " << height << endl
         << "##############################" << endl;

    namedWindow("grey", WINDOW_NORMAL);
    namedWindow("equalized", WINDOW_NORMAL);

    while (1) {
        cap >> image;
        if(image.empty()) exit(1);

        cvtColor(image, grey, CV_BGR2GRAY);

        imshow("grey", grey);

        calcHist(&grey, 1, 0, Mat(), hist, 1, &histSize, &histRange);
        
        // Calculate accumulated histogram
        for (int i = 1; i < hist.rows; ++i) {
            hist.at<float>(i) += hist.at<float>(i-1);
        }
        
        // Normalize the accumulated histogram
        for (int i = 0; i < hist.rows; ++i) {
            hist.at<float>(i) *= 255/((float)(width*height));
        }

        // Repaint the new equalized image
        for (int i = 0; i < height; i++) {
            for (int j = 0; j < width; j++) {
                grey.at<uchar>(i, j) = (uchar) hist.at<float>(grey.at<uchar>(i, j));
            }
        }

        imshow("equalized", grey);
    
        if(waitKey(30) >= 0) break;
    }
    exit(0);
}