doc/tutorials/features2d/feature_detection/feature_detection.markdown

   1 Feature Detection {#tutorial_feature_detection}
   2 =================
   3
   4 Goal
   5 ----
   6
   7 In this tutorial you will learn how to:
   8
   9 -   Use the @ref cv::FeatureDetector interface in order to find interest points. Specifically:
  10     -   Use the cv::xfeatures2d::SURF and its function cv::xfeatures2d::SURF::detect to perform the
  11         detection process
  12     -   Use the function @ref cv::drawKeypoints to draw the detected keypoints
  13
  14 \warning You need the <a href="https://github.com/opencv/opencv_contrib">OpenCV contrib modules</a> to be able to use the SURF features
  15 (alternatives are ORB, KAZE, ... features).
  16
  17 Theory
  18 ------
  19
  20 Code
  21 ----
  22
  23 @add_toggle_cpp
  24 This tutorial code's is shown lines below. You can also download it from
  25 [here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp)
  26 @include samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp
  27 @end_toggle
  28
  29 @add_toggle_java
  30 This tutorial code's is shown lines below. You can also download it from
  31 [here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java)
  32 @include samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java
  33 @end_toggle
  34
  35 @add_toggle_python
  36 This tutorial code's is shown lines below. You can also download it from
  37 [here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py)
  38 @include samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py
  39 @end_toggle
  40
  41 Explanation
  42 -----------
  43
  44 Result
  45 ------
  46
  47 -#  Here is the result of the feature detection applied to the `box.png` image:
  48
  49     ![](images/Feature_Detection_Result_a.jpg)
  50
  51 -#  And here is the result for the `box_in_scene.png` image:
  52
  53     ![](images/Feature_Detection_Result_b.jpg)