Excuse any mistakes in my description as I'm new to ML. But I have an application that takes user input to generate paths/curves (All symbols are single paths) and I would then like to attempt identification. This seems, generally, to be a pretty well studied problem, and there is a lot of reference I can find.
However everything I've found so far starts with some sort of raster format, which makes sense given that often recognition comes in initially in that format. But given my particular set of constraints it seems that there may be additional useful data given that I have paths.
So my question is are there any good techniques for doing identification without first rasterizing my paths that may be well suited for my particular instance, or is rasterizing to a grid particularly well suited to the problem, and should I just raster and solve this problem more classically?