Thinning is a widely used approach for skeletonization. Sequential thinning algorithms use contour tracking: they scan border points and remove the actual one if it is not designated a skeletal point. They may produce various skeletons for different visiting orders. In this paper, we present a new 2-dimensional sequential thinning algorithm, which produces the same result for arbitrary visiting orders and it is capable of extracting maximally thinned skeletons. © Springer-Verlag Berlin Heidelberg 2009.

%B Proceedings of the International Workshop on Combinatorial Image Analysis (IWCIA) %I Springer Verlag %C Playa del Carmen, Mexico %P 162 - 175 %8 Nov 2009 %@ 978-3-642-10208-0 %G eng %U http://link.springer.com/chapter/10.1007/978-3-642-10210-3_13 %9 Conference paper %R 10.1007/978-3-642-10210-3_13 %0 Book Section %B Combinatorial Image Analysis %D 2009 %T Reconstruction of canonical hv-convex discrete sets from horizontal and vertical projections %A Péter Balázs %E Petra Wiederhold %E Reneta P Barneva %XThe problem of reconstructing some special hv-convex discretesets from their two orthogonal projections is considered. In general, the problem is known to be NP-hard, but it is solvable in polynomial time if the discrete set to be reconstructed is also 8-connected. In this paper, we define an intermediate class - the class of hv-convex canonical discrete sets - and give a constructive proof that the above problem remains computationally tractable for this class, too. We also discuss some further theoretical consequences and present experimental results as well. © Springer-Verlag Berlin Heidelberg 2009.

%B Combinatorial Image Analysis %I Springer Verlag %C Berlin; Heidelberg; New York; London; Paris; Tokyo %P 280 - 288 %8 Nov 2009 %@ 978-3-642-10208-0 %G eng %9 Conference paper %R 10.1007/978-3-642-10210-3_22