Feature Description — OpenCV 2.4.10.0 documentation

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# Feature Description

## Goal

In this tutorial you will learn how to:

- Use the DescriptorExtractor interface in order to find the feature vector correspondent to the keypoints. Specifically:
  - Use SurfDescriptorExtractor and its function compute to perform the required calculations.
  - Use a BFMatcher to match the features vector
  - Use the function drawMatches to draw the detected matches.

## Theory

## Code

This tutorial code’s is shown lines below. You can also download it from here

    #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

1. Here is the result after applying the BruteForce matcher between the two original images:

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### Navigation

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- OpenCV Tutorials »
- feature2d module. 2D Features framework »