Added 02 tutorials for Hough Lines and Circle detection in tutorial_code -- based on code existent

samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp

@@ -0,0 +1,55 @@
+/**
+ * @file HoughCircle_Demo.cpp
+ * @brief Demo code for Hough Transform
+ * @author OpenCV team
+ */
+
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+#include <iostream>
+#include <stdio.h>
+
+using namespace cv;
+
+/**
+ * @function main
+ */
+int main(int argc, char** argv)
+{
+   Mat src, src_gray;
+
+   /// Read the image
+   src = imread( argv[1], 1 );
+
+   if( !src.data )
+     { return -1; }
+
+   /// Convert it to gray 
+    cvtColor( src, src_gray, CV_BGR2GRAY );
+
+   /// Reduce the noise so we avoid false circle detection
+    GaussianBlur( src_gray, src_gray, Size(9, 9), 2, 2 );
+
+    vector<Vec3f> circles;
+
+   /// Apply the Hough Transform to find the circles
+    HoughCircles( src_gray, circles, CV_HOUGH_GRADIENT, 1, src_gray.rows/8, 200, 100, 0, 0 );
+
+   /// Draw the circles detected
+    for( size_t i = 0; i < circles.size(); i++ )
+    {
+         Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
+         int radius = cvRound(circles[i][2]);
+         // circle center
+         circle( src, center, 3, Scalar(0,255,0), -1, 8, 0 );
+         // circle outline
+         circle( src, center, radius, Scalar(0,0,255), 3, 8, 0 );
+    }
+
+   /// Show your results 
+    namedWindow( "Hough Circle Transform Demo", CV_WINDOW_AUTOSIZE );
+    imshow( "Hough Circle Transform Demo", src );
+
+    waitKey(0);
+    return 0;
+}