Feature Description

@prev_tutorial{tutorial_feature_detection} @next_tutorial{tutorial_feature_flann_matcher}


Original author	Ana Huamán
Compatibility	OpenCV >= 3.0

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 @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 @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 @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:

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