Feature Description {#tutorial_feature_description} =================== @prev_tutorial{tutorial_feature_detection} @next_tutorial{tutorial_feature_flann_matcher} Goal ---- In this tutorial you will learn how to: - Use the @ref cv::DescriptorExtractor interface in order to find the feature vector correspondent to the keypoints. Specifically: - Use cv::xfeatures2d::SURF and its function cv::xfeatures2d::SURF::compute to perform the required calculations. - Use a @ref cv::DescriptorMatcher to match the features vector - Use the function @ref cv::drawMatches to draw the detected matches. \warning You need the OpenCV contrib modules to be able to use the SURF features (alternatives are ORB, KAZE, ... features). Theory ------ Code ---- @add_toggle_cpp This tutorial code's is shown lines below. You can also download it from [here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp) @include samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp @end_toggle @add_toggle_java This tutorial code's is shown lines below. You can also download it from [here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java) @include samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java @end_toggle @add_toggle_python This tutorial code's is shown lines below. You can also download it from [here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py) @include samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py @end_toggle Explanation ----------- Result ------ Here is the result after applying the BruteForce matcher between the two original images: ![](images/Feature_Description_BruteForce_Result.jpg)