Added Features2D descriptor tutorial + drawMatches in rst

doc/tutorials/features2d/feature_description/feature_description.rst

@@ -0,0 +1,103 @@
+.. _feature_description:
+
+Feature Description
+*******************
+
+Goal
+=====
+
+In this tutorial you will learn how to:
+
+.. container:: enumeratevisibleitemswithsquare
+
+   * Use the :descriptor_extractor:`DescriptorExtractor<>` interface in order to find the feature vector correspondent to the keypoints. Specifically:
+
+     * Use :surf_descriptor_extractor:`SurfDescriptorExtractor<>` and its function :descriptor_extractor:`compute<>` to perform the required calculations.
+     * Use the function :draw_matches:`drawMatches<>` to draw the detected matches.
+     
+
+Theory
+======
+
+Code
+====
+
+This tutorial code's is shown lines below. You can also download it from `here <https://code.ros.org/svn/opencv/trunk/opencv/samples/cpp/tutorial_code/features2D/SURF_descriptor.cpp>`_
+
+.. code-block:: cpp 
+
+   #include <stdio.h>
+   #include <iostream>
+   #include "opencv2/core/core.hpp"
+   #include "opencv2/features2d/features2d.hpp"
+   #include "opencv2/highgui/highgui.hpp"
+
+   using namespace cv;
+
+   void readme();
+
+   /** @function main */
+   int main( int argc, char** argv )
+   {
+     if( argc != 3 )
+      { return -1; }
+
+     Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
+     Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
+  
+     if( !img_1.data || !img_2.data )
+      { return -1; }
+
+     //-- Step 1: Detect the keypoints using SURF Detector
+     int minHessian = 400;
+
+     SurfFeatureDetector detector( minHessian );
+
+     std::vector<KeyPoint> keypoints_1, keypoints_2;
+
+     detector.detect( img_1, keypoints_1 );
+     detector.detect( img_2, keypoints_2 );
+
+     //-- Step 2: Calculate descriptors (feature vectors)
+     SurfDescriptorExtractor extractor;
+
+     Mat descriptors_1, descriptors_2;
+
+     extractor.compute( img_1, keypoints_1, descriptors_1 );
+     extractor.compute( img_2, keypoints_2, descriptors_2 );
+
+     //-- Step 3: Matching descriptor vectors with a brute force matcher
+     BruteForceMatcher< L2<float> > matcher;
+     std::vector< DMatch > matches;
+     matcher.match( descriptors_1, descriptors_2, matches );
+
+     //-- Draw matches
+     Mat img_matches;
+     drawMatches( img_1, keypoints_1, img_2, keypoints_2, matches, img_matches ); 
+
+     //-- Show detected matches
+     imshow("Matches", img_matches );
+
+     waitKey(0);
+
+     return 0;
+     }
+
+    /** @function readme */
+    void readme()
+    { std::cout << " Usage: ./SURF_descriptor <img1> <img2>" << std::endl; }
+
+Explanation
+============
+
+Result
+======
+ 
+#. Here is the result after applying the BruteForce matcher between the two original images:
+ 
+   .. image:: images/Feature_Description_BruteForce_Result.jpg
+      :align: center
+      :height: 200pt
+
+
+