Mat
hough(Mat src) {
	Mat gray;

	// cvtColor(src, gray, COLOR_RGB2GRAY);
	cvtColor(src, src, COLOR_BGR2RGB);
	cvtColor(src, gray, COLOR_RGB2GRAY);

	morph_ellipse(gray);

	vector<Vec3f> circles;

//	minDist Minimum distance between the centers of the detected
//		circles. If the parameter is too small, multiple neighbor
//		circles may be falsely detected in addition to a true one.
//		If it is too large, some circles may be missed.

//	param1 it is the higher threshold of the two passed to the Canny
//		edge detector (the lower one is twice smaller).

//	param2  it is the accumulator threshold for the circle centers at
//		the detection stage. The smaller it is, the more false
//		circles may be detected. Circles, corresponding to the
//		larger accumulator values, will be returned first.

	HoughCircles(gray, circles, HOUGH_GRADIENT, 1,
		// min distance
		// gray.rows / 16,
		track3,

		// canny1
		// 100,
		track1 * 2,

		// canny1 / 2
		// 20,
		track2,

		// min_radius,
		gray.rows / 8 / 8,

		// max_radius
		gray.rows / 8 / 2
		// track3
	);

	const int thresh = track1;
	Canny(gray, src, thresh, thresh * 2, 3);

	cvtColor(src, src, COLOR_GRAY2RGB);

	for (size_t i = 0; i < circles.size(); i++) {

		cv::Scalar color1 = android_green_1;
		cv::Scalar color2 = android_blue_1;

		const int x = circles[i][0];
		const int y = circles[i][1];
		const int r = circles[i][2];

		cv::Point p = Point(x, y);

		circle(src, p, r, color1, 3, LINE_AA);
		circle(src, p, 2, color2, 3, LINE_AA);
	}

	return src;
}