Drawing on Air

Ladies and Gentlemen, I will show you how to make the ultimate-useless-inator!

How to install OpenCV and Visual Studio

Refer to this link to install Visual Studio. After that,

Refer to this link to install the latest OpenCV.

Video

Here is the demo of how it works:

How it works:

So basically it detects the color whose properties you declare in this portion of the code:

//bright yellow properties
int H_MIN = 18;
int H_MAX = 80;
int S_MIN = 94;
int S_MAX = 256;
int V_MIN = 165;
int V_MAX = 256;

H, S, V are Hue, Saturation, and Value, respectively. This color code is similar to the RGB Color Code. To identify the values of it, refer to this video.

Here is the code (objectTrackingTutorial.cpp down below) from the video above that you'll have to run beforehand in order to get the HSV value:

/*
//objectTrackingTutorial.cpp

//Written by  Kyle Hounslow 2013

//Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software")
//, to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, 
//and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

//The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

//THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
//FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 
//LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
//IN THE SOFTWARE.
*/
#include <sstream>
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>

using namespace cv;
using namespace std;

//initial min and max HSV filter values.
//these will be changed using trackbars
int H_MIN = 0;
int H_MAX = 256;
int S_MIN = 0;
int S_MAX = 256;
int V_MIN = 0;
int V_MAX = 256;
//default capture width and height
const int FRAME_WIDTH = 640;
const int FRAME_HEIGHT = 480;
//max number of objects to be detected in frame
const int MAX_NUM_OBJECTS = 50;
//minimum and maximum object area
const int MIN_OBJECT_AREA = 20 * 20;
const int MAX_OBJECT_AREA = FRAME_HEIGHT * FRAME_WIDTH / 1.5;
//names that will appear at the top of each window
const string windowName = "Original Image";
const string windowName1 = "HSV Image";
const string windowName2 = "Thresholded Image";
const string windowName3 = "After Morphological Operations";
const string trackbarWindowName = "Trackbars";
void on_trackbar(int, void*)
{//This function gets called whenever a
	// trackbar position is changed





}
string intToString(int number) {


	std::stringstream ss;
	ss << number;
	return ss.str();
}
void createTrackbars() {
	//create window for trackbars


	namedWindow(trackbarWindowName, 0);
	//create memory to store trackbar name on window
	char TrackbarName[50];
	sprintf_s(TrackbarName, "H_MIN");
	sprintf_s(TrackbarName, "H_MAX");
	sprintf_s(TrackbarName, "S_MIN");
	sprintf_s(TrackbarName, "S_MAX");
	sprintf_s(TrackbarName, "V_MIN");
	sprintf_s(TrackbarName, "V_MAX");
	//create trackbars and insert them into window
	//3 parameters are: the address of the variable that is changing when the trackbar is moved(eg.H_LOW),
	//the max value the trackbar can move (eg. H_HIGH), 
	//and the function that is called whenever the trackbar is moved(eg. on_trackbar)
	//                                  ---->    ---->     ---->      
	createTrackbar("H_MIN", trackbarWindowName, &H_MIN, H_MAX, on_trackbar);
	createTrackbar("H_MAX", trackbarWindowName, &H_MAX, H_MAX, on_trackbar);
	createTrackbar("S_MIN", trackbarWindowName, &S_MIN, S_MAX, on_trackbar);
	createTrackbar("S_MAX", trackbarWindowName, &S_MAX, S_MAX, on_trackbar);
	createTrackbar("V_MIN", trackbarWindowName, &V_MIN, V_MAX, on_trackbar);
	createTrackbar("V_MAX", trackbarWindowName, &V_MAX, V_MAX, on_trackbar);


}
void drawObject(int x, int y, Mat& frame) {

	//use some of the openCV drawing functions to draw crosshairs
	//on your tracked image!

	//UPDATE:JUNE 18TH, 2013
	//added 'if' and 'else' statements to prevent
	//memory errors from writing off the screen (ie. (-25,-25) is not within the window!)

	circle(frame, Point(x, y), 20, Scalar(0, 255, 0), 2);
	if (y - 25 > 0)
		line(frame, Point(x, y), Point(x, y - 25), Scalar(0, 255, 0), 2);
	else line(frame, Point(x, y), Point(x, 0), Scalar(0, 255, 0), 2);
	if (y + 25 < FRAME_HEIGHT)
		line(frame, Point(x, y), Point(x, y + 25), Scalar(0, 255, 0), 2);
	else line(frame, Point(x, y), Point(x, FRAME_HEIGHT), Scalar(0, 255, 0), 2);
	if (x - 25 > 0)
		line(frame, Point(x, y), Point(x - 25, y), Scalar(0, 255, 0), 2);
	else line(frame, Point(x, y), Point(0, y), Scalar(0, 255, 0), 2);
	if (x + 25 < FRAME_WIDTH)
		line(frame, Point(x, y), Point(x + 25, y), Scalar(0, 255, 0), 2);
	else line(frame, Point(x, y), Point(FRAME_WIDTH, y), Scalar(0, 255, 0), 2);

	putText(frame, intToString(x) + "," + intToString(y), Point(x, y + 30), 1, 1, Scalar(0, 255, 0), 2);

}
void morphOps(Mat& thresh) {

	//create structuring element that will be used to "dilate" and "erode" image.
	//the element chosen here is a 3px by 3px rectangle

	Mat erodeElement = getStructuringElement(MORPH_RECT, Size(3, 3));
	//dilate with larger element so make sure object is nicely visible
	Mat dilateElement = getStructuringElement(MORPH_RECT, Size(8, 8));

	erode(thresh, thresh, erodeElement);
	erode(thresh, thresh, erodeElement);


	dilate(thresh, thresh, dilateElement);
	dilate(thresh, thresh, dilateElement);



}
void trackFilteredObject(int& x, int& y, Mat threshold, Mat& cameraFeed) {

	Mat temp;
	threshold.copyTo(temp);
	//these two vectors needed for output of findContours
	vector< vector<Point> > contours;
	vector<Vec4i> hierarchy;
	//find contours of filtered image using openCV findContours function
	findContours(temp, contours, hierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE);
	//use moments method to find our filtered object
	double refArea = 0;
	bool objectFound = false;
	if (hierarchy.size() > 0) {
		int numObjects = hierarchy.size();
		//if number of objects greater than MAX_NUM_OBJECTS we have a noisy filter
		if (numObjects < MAX_NUM_OBJECTS) {
			for (int index = 0; index >= 0; index = hierarchy[index][0]) {

				Moments moment = moments((cv::Mat)contours[index]);
				double area = moment.m00;

				//if the area is less than 20 px by 20px then it is probably just noise
				//if the area is the same as the 3/2 of the image size, probably just a bad filter
				//we only want the object with the largest area so we safe a reference area each
				//iteration and compare it to the area in the next iteration.
				if (area > MIN_OBJECT_AREA && area<MAX_OBJECT_AREA && area>refArea) {
					x = moment.m10 / area;
					y = moment.m01 / area;
					objectFound = true;
					refArea = area;
				}
				else objectFound = false;


			}
			//let user know you found an object
			if (objectFound == true) {
				putText(cameraFeed, "Tracking Object", Point(0, 50), 2, 1, Scalar(0, 255, 0), 2);
				//draw object location on screen
				drawObject(x, y, cameraFeed);
			}

		}
		else putText(cameraFeed, "TOO MUCH NOISE! ADJUST FILTER", Point(0, 50), 1, 2, Scalar(0, 0, 255), 2);
	}
}
int main(int argc, char* argv[])
{
	//some boolean variables for different functionality within this
	//program
	bool trackObjects = false;
	bool useMorphOps = false;
	//Matrix to store each frame of the webcam feed
	Mat cameraFeed;
	//matrix storage for HSV image
	Mat HSV;
	//matrix storage for binary threshold image
	Mat threshold;
	//x and y values for the location of the object
	int x = 0, y = 0;
	//create slider bars for HSV filtering
	createTrackbars();
	//video capture object to acquire webcam feed
	VideoCapture capture;
	//open capture object at location zero (default location for webcam)
	capture.open(0);
	//set height and width of capture frame
	capture.set(CAP_PROP_FRAME_WIDTH, FRAME_WIDTH);
	capture.set(CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT);
	//start an infinite loop where webcam feed is copied to cameraFeed matrix
	//all of our operations will be performed within this loop
	while (1) {
		//store image to matrix
		capture.read(cameraFeed);
		//convert frame from BGR to HSV colorspace
		cvtColor(cameraFeed, HSV, COLOR_BGR2HSV);
		//filter HSV image between values and store filtered image to
		//threshold matrix
		inRange(HSV, Scalar(H_MIN, S_MIN, V_MIN), Scalar(H_MAX, S_MAX, V_MAX), threshold);
		//perform morphological operations on thresholded image to eliminate noise
		//and emphasize the filtered object(s)
		if (useMorphOps)
			morphOps(threshold);
		//pass in thresholded frame to our object tracking function
		//this function will return the x and y coordinates of the
		//filtered object
		if (trackObjects)
			trackFilteredObject(x, y, threshold, cameraFeed);

		//show frames 
		imshow(windowName2, threshold);
		imshow(windowName, cameraFeed);
		imshow(windowName1, HSV);


		//delay 30ms so that screen can refresh.
		//image will not appear without this waitKey() command
		waitKey(30);
	}






	return 0;
}

All you have to do is slide the trackbars

until the only remaining white parts of the "Thresholded Image" windows are correspondent to the object that you want to detect in real life. For example, if you want to detect the yellow sharpie, you'll have to slide the trackbars so that the white parts of the "Thresholded Image" windows are actually the threshold image of the yellow sharpie. Again, if you find my wording hard to understand (which I know it is), refer back to the video to see how it's done.

After you get the HSV value to want, save it somewhere for near future reference.

Then, run the "webcam.cpp" code down below. Remember to change this portion

//bright yellow properties
int H_MIN = 18;
int H_MAX = 80;
int S_MIN = 94;
int S_MAX = 256;
int V_MIN = 165;
int V_MAX = 256;

into whatever HSV value you found previously.

Then hit the "Debug" button or F5 button to draw!