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Features2D + Homography to find a known object {#tutorial_feature_homography}
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==============================================
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@prev_tutorial{tutorial_feature_flann_matcher}
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@next_tutorial{tutorial_detection_of_planar_objects}
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| Original author | Ana Huamán |
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| Compatibility | OpenCV >= 3.0 |
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Goal
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----
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In this tutorial you will learn how to:
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- Use the function @ref cv::findHomography to find the transform between matched keypoints.
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- Use the function @ref cv::perspectiveTransform to map the points.
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\warning You need the <a href="https://github.com/opencv/opencv_contrib">OpenCV contrib modules</a> to be able to use the SURF features
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(alternatives are ORB, KAZE, ... features).
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Theory
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------
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Code
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----
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@add_toggle_cpp
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.cpp)
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@include samples/cpp/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.cpp
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@end_toggle
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@add_toggle_java
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java)
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@include samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java
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@end_toggle
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@add_toggle_python
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py)
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@include samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py
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@end_toggle
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Explanation
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-----------
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Result
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------
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- And here is the result for the detected object (highlighted in green). Note that since the homography is estimated with a RANSAC approach,
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detected false matches will not impact the homography calculation.
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![](images/Feature_Homography_Result.jpg)
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