Doxygen tutorials: basic structure

doc/tutorials/features2d/feature_detection/feature_detection.markdown

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+Feature Detection {#tutorial_feature_detection}
+=================
+
+Goal
+----
+
+In this tutorial you will learn how to:
+
+-   Use the @ref cv::FeatureDetector interface in order to find interest points. Specifically:
+    -   Use the @ref cv::SurfFeatureDetector and its function @ref cv::detect to perform the
+        detection process
+    -   Use the function @ref cv::drawKeypoints to draw the detected keypoints
+
+Theory
+------
+
+Code
+----
+
+This tutorial code's is shown lines below.
+@code{.cpp}
+#include <stdio.h>
+#include <iostream>
+#include "opencv2/core.hpp"
+#include "opencv2/features2d.hpp"
+#include "opencv2/xfeatures2d.hpp"
+#include "opencv2/highgui.hpp"
+
+using namespace cv;
+using namespace cv::xfeatures2d;
+
+void readme();
+
+/* @function main */
+int main( int argc, char** argv )
+{
+  if( argc != 3 )
+  { readme(); return -1; }
+
+  Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE );
+  Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE );
+
+  if( !img_1.data || !img_2.data )
+  { std::cout<< " --(!) Error reading images " << std::endl; return -1; }
+
+  //-- Step 1: Detect the keypoints using SURF Detector
+  int minHessian = 400;
+
+  Ptr<SURF> detector = SURF::create( minHessian );
+
+  std::vector<KeyPoint> keypoints_1, keypoints_2;
+
+  detector->detect( img_1, keypoints_1 );
+  detector->detect( img_2, keypoints_2 );
+
+  //-- Draw keypoints
+  Mat img_keypoints_1; Mat img_keypoints_2;
+
+  drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
+  drawKeypoints( img_2, keypoints_2, img_keypoints_2, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
+
+  //-- Show detected (drawn) keypoints
+  imshow("Keypoints 1", img_keypoints_1 );
+  imshow("Keypoints 2", img_keypoints_2 );
+
+  waitKey(0);
+
+  return 0;
+  }
+
+  /* @function readme */
+  void readme()
+  { std::cout << " Usage: ./SURF_detector <img1> <img2>" << std::endl; }
+@endcode
+Explanation
+-----------
+
+Result
+------
+
+1.  Here is the result of the feature detection applied to the first image:
+
+    ![image](images/Feature_Detection_Result_a.jpg)
+
+2.  And here is the result for the second image:
+
+    ![image](images/Feature_Detection_Result_b.jpg)
+
+