Hi there!
I am trying to do detection of particles using OpenCV:
So far, I have been able to threshold the image (video) based on intensity. However, currently I am trying to use kmean to detect the oval shape particles, but to no avail. I need some help with the coding for the kmeans; I have scoured through OpenCV help pages, but yet to no avail. Will greatly appreciate help! Thank you very much
// Step 1: Obtain Ultrasound image // Step 2: Convert to black and white image // Step 3: Threshold video based on B&W intensity // Step 4: Use plusstring algorithm to find centroids of clusters // e.g. K-mean plus string algorithm // Step 5: Appoint center to each cluster // Step 6: Tracking algorithm: Kalman filter // Step 7: Output: Draw circle around particle
include "stdafx.h"
include<opencv cvaux.h="">
include<opencv highgui.h="">
include<opencv cxcore.h="">
//#include "opencv/cv.h" //#include "opencv/highgui.h" //#include "opencv/cxcore.h"
include "opencv2/highgui/highgui.hpp"
include <iostream>
include<stdio.h>
include<stdlib.h>
define THRESHOLDING
using namespace cv;
using namespace std;
int main(int argc, char* argv[])
{
VideoCapture cap("C:\\BubbleCut.avi"); // open the video file for reading
if (!cap.isOpened()) // if not success, exit program
{
cout << "Cannot open the video file" << endl;
return -1;
}
//Step: Declare all Mat
Mat frame;
Mat frame_grey;
Mat frame_thresholded; //to give binary image 0-255
Mat frame_houghtrans; //Canny edge gives a binary image too
Mat labels;
Mat data, centers;
vector<Vec3f> circles;
//cap.set(CV_CAP_PROP_POS_MSEC, 300); //start the video at 300ms
double fps = cap.get(CV_CAP_PROP_FPS); //get the frames per seconds of the video
cout << "Frame per seconds : " << fps << endl;
//namedWindow("MyVideo", CV_WINDOW_AUTOSIZE); create a window called "MyVideo" can be omitted
while (1)
{
cap >> frame; //replace lines: receive frame from cap and store into Mat object aka frame
if (frame.empty())
{
cout << "End of file" << endl << endl;
cap.release(); //not necessary
break;
}
//Step _ : Convert ultrasound raw video into greyscale video
cvtColor(frame, frame_grey, COLOR_RGB2GRAY);
//plusstring algorithm, blob detection or hough transform
#ifdef THRESHOLDING
adaptiveThreshold(frame_grey, frame_thresholded, 255, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 45, 0);
#endif
// Step 4: Use plusstring algorithm to find centroids of clusters
// e.g. K-mean plus string algorithm, find parameter of circle
**//kmeans(frame_thresholded, 8, labels, TermCriteria(CV_TERMCRIT_ITER, 10, 1.0), 3, KMEANS_PP_CENTERS, centers);**
// Step 7: Display: Videos
imshow("Raw video", frame); //show the frame in "MyVideo" window
imshow("Thresholded", frame_thresholded);
if (waitKey(30) == 27) //wait for 'esc' key press for 30 ms. If 'esc' key is pressed, break loop
{
cout << "esc key is pressed by user" << endl;
break;
}
}
return 0;
}
