Feature points in image, Keypoint extraction

Finds, matches, plots feature points in images.
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Mise à jour 28 août 2015

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Feature points (read corners) in images are points that invariant under view changes, zoom, lightening conditions etc.

These code has been written as part of the project I have performed in image processing course some time ago.
The code should (hopefully) be easily readable since it has been well commented, with report for background information and additional explanation.
Hope it will be useful for students entering the image processing field.
Implemented a SIFT like descriptor, as well as ASIFT (http://www.cmap.polytechnique.fr/~yu/research/ASIFT/demo.html).
Shortly about ASIFT - simulates view changes of images, for each such view finds FPs followed by descriptor calculation for future matching. It is slow and intended for studying purposes. Quick C++ implementation is available at the authors aforementioned ASIFT-project page.

There are a lot of options, parameters to control every step of calculations. Try to play with it: the performance may vary drastically.

Used pdist2.m code from Piotr's Toolbox
http://vision.ucsd.edu/~pdollar/toolbox/doc/
as well k nearest neighbors from Matlab exchange server, author of which I can't find now.

Citation pour cette source

Artiom Kovnatsky (2024). Feature points in image, Keypoint extraction (https://www.mathworks.com/matlabcentral/fileexchange/29004-feature-points-in-image-keypoint-extraction), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2008a
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Inspiré par : Keypoint Extraction

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Version Publié le Notes de version
1.1.0.0

- fixed bug in code (the one noticed by the users)
- description

1.0.0.0