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--- opencv_tutorials_t3 [2016/06/06 16:18] – joaomatos
+++ opencv_tutorials_t3 [2017/05/13 17:20] (current) – [Detecting Circles on Webcam] acater
@@ Line 6: / Line 6: @@
 {{::detecting_circle_image.rar|Detecting Circles on Image}}
+{{::detecting_circles_on_webcam.rar|Detecting Circles on Webcam}}
-{{ ::circledetec.jpg?direct |}}
 ----
-===== Code =====
+===== Detecting Circles in Image =====
+{{ ::circledetec.jpg?direct |}}
 <Code:c++ linenums:1>
@@ Line 268: / Line 272: @@
 Now we open a window and display the image with the draw on it. We put a different name from the first window so we open two different windows to display the original image and the image with the detected circle.
+----
+===== Detecting Circles on Webcam =====
+{{ ::circle_webcam.jpg?direct |}}
+<Code:c++ linenums:1>
+#include <sstream>
+#include <string>
+#include <iostream>
+#include <opencv/highgui.h>
+#include <opencv/cv.h>
+#include <opencv2/core/core.hpp>
+#include <opencv2/highgui/highgui.hpp>
+#include <opencv2/imgproc/imgproc.hpp>
+using namespace cv;
+using namespace std;
+String intToString(int number)
+{
+	std::stringstream ss;
+	ss << number;
+	return ss.str();
+}
+int main()
+{
+	//Varibles to store and show the detected circle properties
+	string radiusStr;
+	string xcenterStr;
+	string ycenterStr;
+	int Rvalue;
+	int Xvalue;
+	int Yvalue;
+	//Variables to store the webcam video , and a converted version of the video
+	Mat coloredimage;
+	Mat grayimage;
+	//auxiliar variable to quit the loop and end the program
+	char key = 0;
+	//Open the default camera
+	VideoCapture capture(0);
+	//Check for Failure
+	if (!capture.isOpened())
+	{
+		printf("Failed to open the webcam");
+	}
+	//Set Capture device properties.
+	capture.set(CV_CAP_PROP_FRAME_WIDTH, 640);
+	capture.set(CV_CAP_PROP_FRAME_HEIGHT, 480);
+	//Loop will stop if "q" is pressed in the keyboard
+	while (key != 'q')
+	{
+		//Capture a frame of the webcam live video and store it on the image variable
+		capture >> coloredimage;
+		//Resize this frame and convert to gray scale
+		cvtColor(coloredimage, grayimage, CV_BGR2GRAY);
+		// Apply blur to Reduce the noise so we avoid false circle detection
+		GaussianBlur(grayimage, grayimage, Size(9, 9), 2, 2);
+		//create a vector to store the center value ( x and y coordinates ) and the radius of each detected circle
+		vector<Vec3f> circles;
+		// Apply the Hough Transform to find the circles (use the gray scale image as input)
+		//Arguments: 1: input image( grayscaled ) . 2: vector to tore the circle parameters .3: detection method,
+		// 4: inverse ratio of resolution . 5 minimum distance between detected centers. 6: upper threshold for the internal canny edge detector
+		//7: threshold for center detection . 8: Minimum radius to be detected (0=unknown) . 9: maximum radius to be detected
+		HoughCircles(grayimage, circles, CV_HOUGH_GRADIENT, 1, 30, 200, 50, 0, 0);
+		// Draw the circles detected
+		for (size_t i = 0; i < circles.size(); i++)
+		{
+			//Get the informations from the circles vector generated by the function HoughCircles.
+			//Column is circles[i][0]  , Row is circles[i][1] , radius is circles[i][2]
+			Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
+			int radius = cvRound(circles[i][2]);
+			//Store these values into variables to be converted into string and displayed on the image
+			Rvalue = radius;
+			Xvalue = cvRound(circles[i][0]);
+			Yvalue = cvRound(circles[i][1]);
+			//DRAWING THE CENTER OF THE CIRCLE
+			//Use the circle function to draw the center of the detected circle
+			//Use the center coordinate and a radius of 3 to just draw a point on the center.
+			circle(coloredimage, center, 3, Scalar(0, 255, 0), -1, 8, 0);
+			//DRAWING THE CIRCLE CONTOUR.
+			//Use the circle function to draw the detected circle on the image
+			//Use the center coordinate and the radius coordinate detected by the HoughCircles function
+			circle(coloredimage, center, radius, Scalar(0, 0, 255), 3, 8, 0);
+			//Convert the integer Center point and radius values to string
+			radiusStr = intToString(Rvalue);
+			xcenterStr = intToString(Xvalue);
+			ycenterStr = intToString(Yvalue);
+			//Display on the colored image the center and radius values.
+			putText(coloredimage, "(" + xcenterStr + "," + ycenterStr + ")", Point(Xvalue, Yvalue-20), 1, 1, Scalar(0, 255, 0), 2);
+			//Display the values also on the cmd window
+			cout << "center : " << center << "\nradius : " << radius << endl;
+		}
+		// Show your results
+		namedWindow("Hough Circle Transform Demo", CV_WINDOW_AUTOSIZE);
+		imshow("Hough Circle Transform Demo", coloredimage);
+		key = waitKey(25);
+	}
+	return 0;
+}
+</Code>
+The idea to change from an image to the webcam video is the same used on the Tutorial 1. We change the **"imread"** for the **"VideoCapture**" and change the **"resize"** for the **"capture.set"**.  We use a loop until the q key is pressed to display the frames on the window.Our colored image is set using **"capture >> coloredimage;"** and all the following procedure to detect the circle is the same from the image code ( because we will analyze frame by frame ).
+\\
+\\
+Below is a video demonstrating the first program in real time.
+{{youtube>doq8hqEDhY0?medium}}
+\\
+\\Below is a video demonstrating the second program in real time.
+{{youtube>htymt5vIA3M?medium}}