Image Stitching for NVIDIA Jetson - User Guide - Homography estimation
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The following page will introduce a way to estimate an initial homography matrix that can be used in the cudastitcher element. This method consists of a Python script that estimates the homography between two images.
Dependencies
- Python 3.6
- OpenCV 4.0 or later.
- Numpy
Script estimation flow
The steps performed by the script are the following:
- Load the images.
- Remove the distortion of the images.
- Perform a preprocessing to the images removing the noise using a Gaussian filter.
- Extract the keypoint and the corresponding descriptors with the SIFT algorithm.
- Find the correspondences among the key points of the two images.
- With the resulting keypoints, estimate the homography.
Script usage
The script has two modes:
- left_fixed: where the left image is fixed and the right image will be transformed by the homography.
- right_fixed: where the right image is fixed and the left image will be transformed by the homograpy.
For both modes can be adjusted the sigma value of the Gaussian filter and the width size of the overlap between the two images. The following are the complete options of the script:
python homography_estimation.py --help
usage: homography_estimation.py [-h] {left_fixed,right_fixed} ...
Tool for use the prediction capabilities of the models in the Adversarial
Anomaly Detector.
positional arguments:
{left_fixed,right_fixed}
left_fixed Estimation of homography between two images
right_fixed Estimation of homographies two images
optional arguments:
-h, --help show this help message and exit
Type "homography_estimation.py <command> -h" for more information.
