Splines (bill theory of OCR)

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.

1. measure correspondence of overlapping segments of splines.
2. 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.
3. Assume there are building blocks of shapes, break each spline into it's fundamental composition of shapes.
4. the input is also not just one spline, but could be several different spline interpretations.

Edit 2: Syndrome's apparently is what I need. I'll make sure to remember that when I take the class.

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.

Numerical Geometry of non-rigid shapes

Numerical Geometry of Images

Learning OpenCV

NURBS

Gestalt