SnakeOptimizerSingleVarCalc: Image Segmentation based on Variational Calculus

Parametric activce contours represent contours as sets of discrete 2D points. Based on application specific energy functionals image segmentation is accomplished by minimizing the functionals with common methods from numerical mathmatics. This optimizer for snake-based image segmentation applies methods from variational calculus to solve the optimization problem, i.e. uses Euler-Lagrange equations and gradient descent techniques. It evolves a single snake in a given image.

Reference:

Michael Kass, Andrew Witkin and Demetri Terzopoulos,
"Snakes: Active contour models",
Int. Journal of Computer Vision, vol. 1, no. 4, pp. 321-331, 1988.

Required input:

Optional input:

Supplemental parameters:

Output:

The operator returns...

Note that the snake optimizer allows for interaction. At the bottom of the control window there are buttons to pause/resume the optimizer during segmentation or to run it step-wise.