To preface this, I have only read wiki articles, and have barely skimmed them at that.
Given an experimentally found spline $S_1$ and a two dimensional spline array $SA$, we want to find the "closest fit" spline for $S_1$. The structure of $SA$ is such that each column $c$ has multiple forms of a given spline $S_c$.
Alright, and I want to apply BCH codes to do this. I'm going to take coding theory next semester, so I guess I'll just wait until then to think about this more.
Edit 1: I just came up with two ideas while laying in bed, among others coming to me right now.
- measure correspondence of overlapping segments of splines.
- Create a 3 dimensional graph with the z being the first derivative of the spline, another with the z being the 2nd derivative, and another with the z being the 3rd derivative.
- Assume there are building blocks of shapes, break each spline into it's fundamental composition of shapes.
- the input is also not just one spline, but could be several different spline interpretations.
Edit 3(March 13, 2010): Computer Vision is a pretty large field, and this is a very mathematical approach to it, so I think I should read and play with these things before I see where this approach fits into this quite large field.