opencv/doc/tutorials/features2d/feature_description/feature_description.rst
2013-08-21 18:59:25 +04:00

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.. _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 a :brute_force_matcher:`BFMatcher<>` to match the features vector
* 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 <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/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"
#include "opencv2/nonfree/features2d.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
BFMatcher matcher(NORM_L2);
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