Active contours using a constraint-based implicit representation

We present a new constraint-based implicit active contour, which shares desirable properties of both parametric and implicit active contours. Like parametric approaches, their representation is compact and can be manipulated interactively. Like other implicit approaches, they can naturally adapt to nonsimple topologies. Unlike implicit approaches using level-set methods, representation of the contour does not require a dense mesh. Instead, it is based on specified on-curve and off-curve constraints, which are interpolated using radial basis functions. These constraints are evolved according to specified forces drawn from the relevant literature of both parametric and implicit approaches. This new type of active contour is demonstrated through synthetic images, photographs, and medical images with both simple and nonsimple topologies. For complex input, this approach produces results comparable to those of level set or parameterized finite-element active models, but with a compact analytic representation. As with other active contours they can also be used for tracking, especially for multiple objects that split or merge.