The ripple filter: an algorithm for region growing in scene agalysis

This paper deals with the software implementa tion of a new type of region grower for object boundary finding when the boundaries are highly variable and the images very noisy. The approach is both structural and probabilistic and consists of data modeling followed by boundary finding through statistical estimation realized as cost functional minimization. The algorithm, involving a first guess at the boundary followed by successively improving approximations, is described, and also described is its implementation and experimental results.