Classification : Hu and Zernike moments

Overview of Hu and Zernike moments for shape recognition in computer vision applications. Provides Matlab implementations of these transformation-invariant descriptors used for object classification.

Classification : Hu and Zernike moments
Photo by Trevor Vannoy / Unsplash

Hi all,

I am currently working on a Computer Vision application which requires a step of shape recognition. And I have been searching for lots of different parameters allowing to precisely classify objects afterwards.

In a lot of applications, one need parameters that are invariant to linear transformations (that is translation, rotation and scaling) to ease object classification in various conditions.

If you search for such parameters, you will quickly hear the name of Zernicke and Hu moments.  Here are links to a Matlab implementation of those descriptors:

Have fun using it, but don't forget to mention their previous authors ;).

And if you need more descriptors in your classification, here is a quite exhaustive list (at least as much as it can be).

If I have some spare time, I might think of a Pythonic implementation one day ^^. I'll let you know.

Hope you'll enjoy ;)

See you