Re:Why do CNNs generalize so poorly to small image transform...
by magicalhippo on Monday June 11, 2018 @11:09AM
(#17284886)
Having dabbled with image processing, your comment reminded me of the Fourier Mellin transform, which can be used for translation, rotation and scale invariant feature detection.
I did a quick search and came up with this paper[1], and while they don't use the Fourier-Mellin transform, they do use a log-polar transform[2], where rotation and scaling are transformed to translations. This, they claim, result in much improved classification of rotated and scaled data.
I haven't been keeping up on the latest in the ML field tho, so maybe it's rubbish, but like you I'd be surprised if some extra processing doesn't play a role.
I did a quick search and came up with this paper[1], and while they don't use the Fourier-Mellin transform, they do use a log-polar transform[2], where rotation and scaling are transformed to translations. This, they claim, result in much improved classification of rotated and scaled data.
I haven't been keeping up on the latest in the ML field tho, so maybe it's rubbish, but like you I'd be surprised if some extra processing doesn't play a role.
[1]: https://arxiv.org/abs/1709.01889
[2]: https://sthoduka.github.io/imreg_fmt/docs/log-polar-transfor...