Topic
Distance transform
About: Distance transform is a research topic. Over the lifetime, 2886 publications have been published within this topic receiving 59481 citations.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: In this paper, an efficient Voronoi transform algorithm for constructing Voroni diagrams using segment lists of rows has been proposed, which takes segments rather than pixels as the basic units to represent and propagate the nearest neighbor information.
Abstract: We propose an efficient Voronoi transform algorithm for constructing Voronoi diagrams using segment lists of rows. A significant feature of the algorithm is that it takes segments rather than pixels as the basic units to represent and propagate the nearest neighbor information. The segment lists are dynamically updated as they are scanned. A distance map can then be easily computed from the segment list representation of the Voronoi diagram. Experimental results have demonstrated its high efficiency. Extension of the algorithm to higher dimensions is also discussed.
48 citations
••
20 Jun 2009TL;DR: A new approach for detecting low textured planar objects and estimating their 3D pose by introducing distance transform templates, generated by applying the distance transform to standard edge based templates and obtaining robustness against perspective transformations by training a classifier for various template poses.
Abstract: We propose a new approach for detecting low textured planar objects and estimating their 3D pose. Standard matching and pose estimation techniques often depend on texture and feature points. They fail when there is no or only little texture available. Edge-based approaches mostly can deal with these limitations but are slow in practice when they have to search for six degrees of freedom. We overcome these problems by introducing the distance transform templates, generated by applying the distance transform to standard edge based templates. We obtain robustness against perspective transformations by training a classifier for various template poses. In addition, spatial relations between multiple contours on the template are learnt and later used for outlier removal. At runtime, the classifier provides the identity and a rough 3D pose of the distance transform template, which is further refined by a modified template matching algorithm that is also based on the distance transform. We qualitatively and quantitatively evaluate our approach on synthetic and real-life examples and demonstrate robust real-time performance.
48 citations
••
TL;DR: The method is demonstrated by the segmentation of the human brain from three-dimensional magnetic resonance images of the head given an a priori model of a normal brain.
48 citations
••
TL;DR: A method is described that reduces the set of centres of maximal discs/spheres, that represents a shape, under the constraint that the shape can be exactly reconstructed using the reverse distance transformation.
47 citations
••
TL;DR: The proposed algorithm constitutes a unified methodology that can be applied to any discrete moment family in the same way and produces similar promising results, as has been concluded through a detailed experimental investigation.
47 citations