OpenCV/opencv/doc/tutorials/features2d/feature_detection/feature_detection.markdown

Feature Detection {#tutorial_feature_detection}

@tableofcontents

@prev_tutorial{tutorial_corner_subpixels} @next_tutorial{tutorial_feature_description}

| | | | -: | :- | | Original author | Ana Huamán | | Compatibility | OpenCV >= 3.0 |

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 @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 @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 @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)