Computer Vision Again
•Divide P.O. approaches into two groups.
•Parametric: We have a description of what we want, with parameters:
–Examples: lines, circles, constant intensity, constant intensity + Gaussian noise.
•Non-parametric: We have constraints the group should satisfy, or optimality criteria.
–Example: SNAKES.  Find the closed curve that is smoothest and that also best follows strong image gradients.