Feature Detection {#tutorial_feature_detection} ================= Goal ---- In this tutorial you will learn how to: - Use the @ref cv::FeatureDetector interface in order to find interest points. Specifically: - Use the cv::xfeatures2d::SURF and its function cv::xfeatures2d::SURF::detect to perform the detection process - Use the function @ref cv::drawKeypoints to draw the detected keypoints \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_detection/SURF_detection_Demo.cpp) @include samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_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_detection/SURFDetectionDemo.java) @include samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.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_detection/SURF_detection_Demo.py) @include samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py @end_toggle Explanation ----------- Result ------ -# Here is the result of the feature detection applied to the `box.png` image: ![](images/Feature_Detection_Result_a.jpg) -# And here is the result for the `box_in_scene.png` image: ![](images/Feature_Detection_Result_b.jpg)