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.

JF - Proceedings of the International Workshop on Combinatorial Image Analysis (IWCIA) PB - Springer Verlag CY - Playa del Carmen, Mexico SN - 978-3-642-10208-0 UR - http://link.springer.com/chapter/10.1007/978-3-642-10210-3_13 N1 - ScopusID: 78650496028doi: 10.1007/978-3-642-10210-3_13 ER - TY - CHAP T1 - Reconstruction of canonical hv-convex discrete sets from horizontal and vertical projections T2 - Combinatorial Image Analysis Y1 - 2009 A1 - Péter Balázs ED - Petra Wiederhold ED - Reneta P Barneva AB -The 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.

JF - Combinatorial Image Analysis PB - Springer Verlag CY - Berlin; Heidelberg; New York; London; Paris; Tokyo SN - 978-3-642-10208-0 N1 - UT: 000279344100022ScopusID: 78650444641doi: 10.1007/978-3-642-10210-3_22 ER -