Skeleton Extracting Algorithm via Optimized Discrete λ-Medial Axis

The discrete λ-medial axis（DLMA） is a fast and robust medial axis transformation.It can be applied in extracting single-pixel accurate skeletons.But an appropriate parameter λ is needed to set in advance.Meanwhile,it relies on the single threshold filters.Thus,it is hard to select the highly adaptive parameter λ,when the shapes have complex topology.We propose a method combining the local maxima of Euclidean distance transform and the idea of background space.The proposed algorithm divides the DLMA algorithm into two steps.Firstly,a small λ threshold is used to obtain the rough skeleton and the N₄ neighborhood is reduced to N₂ neighborhood.Secondly,a strategy with the automatic adjustment of threshold is designed to ensure that the skeleton growth is well adaptable to the change of the width of the shape.The experimental results showed that the proposed optimized algorithm is more adaptable,faster and more robust.