sample.cpp

// Program to display a video from attached default camera device and detect colored blobs using H and S thresholding
// Remove noise using opening and closing morphological operations
// Author: Samarth Manoj Brahmbhatt, University of Pennsylvania

 
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
 
using namespace cv;
using namespace std;
 
int hs_slider = 0, low_slider = 30, high_slider = 100;
int low_h = 30, low_s = 30, high_h = 100, high_s = 100;
 
void on_hs_trackbar(int, void *) {
    switch(hs_slider) {
        case 0:
            cv::setTrackbarPos("Low threshold", "Segmentation", low_h);
            cv::setTrackbarPos("High threshold", "Segmentation", high_h);
            break;
        case 1:
            cv::setTrackbarPos("Low threshold", "Segmentation", low_s);
            cv::setTrackbarPos("High threshold", "Segmentation", high_s);
            break;
    }
}
 
void on_low_thresh_trackbar(int, void *) {
    switch(hs_slider) {
        case 0:
            low_h = min(high_slider - 1, low_slider);
            cv::setTrackbarPos("Low threshold", "Segmentation", low_h);
            break;
        case 1:
            low_s = min(high_slider - 1, low_slider);
            cv::setTrackbarPos("Low threshold", "Segmentation", low_s);
            break;
    }
}
 
void on_high_thresh_trackbar(int, void *) {
    switch(hs_slider) {
        case 0:
            high_h = max(low_slider + 1, high_slider);
            cv::setTrackbarPos("High threshold", "Segmentation", high_h);
            break;
        case 1:
            high_s = max(low_slider + 1, high_slider);
            cv::setTrackbarPos("High threshold", "Segmentation", high_s);
            break;
    }
}
 
int main()
{
    // Create a VideoCapture object to read from video file
    // 0 is the ID of the built-in laptop camera, change if you want to use other camera
    VideoCapture cap(1);
     
    //check if the file was opened properly
    if(!cap.isOpened())
    {
            cout << "Capture could not be opened succesfully" << endl;
            return -1;
    }
 
    cv::namedWindow("Video");
    cv::namedWindow("Segmentation");
 
    cv::createTrackbar("0. H\n1. S", "Segmentation", &hs_slider, 1, on_hs_trackbar);
    cv::createTrackbar("Low threshold", "Segmentation", &low_slider, 255, on_low_thresh_trackbar);
    cv::createTrackbar("High threshold", "Segmentation", &high_slider, 255, on_high_thresh_trackbar);
     
    while(char(waitKey(1)) != 'q' && cap.isOpened())
    {
        cv::Mat frame, frame_thresholded, frame_hsv;
                     
        cap >> frame;
 
        cv::cvtColor(frame, frame_hsv, CV_BGR2HSV);
 
        // Check if the video is over
        if(frame.empty())
        {
                cout << "Video over" << endl;
                break;
        }
         
        // extract the Hue and Saturation channels
        int from_to[] = {0,0, 1,1};
        Mat hs(frame.size(), CV_8UC2);
        cv::mixChannels(&frame_hsv, 1, &hs, 1, from_to, 2);
 
        // check the image for a specific range of H and S
        cv::inRange(hs, Scalar(low_h, low_s), Scalar(high_h, high_s), frame_thresholded);
 
        // open and close to remove noise
        cv::Mat str_el = getStructuringElement(MORPH_ELLIPSE, Size(7, 7));
        cv::morphologyEx(frame_thresholded, frame_thresholded, MORPH_OPEN, str_el);
        cv::morphologyEx(frame_thresholded, frame_thresholded, MORPH_CLOSE, str_el);
         
        cv::imshow("Video", frame);
        cv::imshow("Segmentation", frame_thresholded);
    }
 
    return 0;
}