2.0 KiB
Feature Detection
@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:

-# And here is the result for the box_in_scene.png
image:
