A 3D fully parallel surface-thinning algorithm

Palágyi, Kálmán

doi:10.1016/j.tcs.2008.06.041

Cited by 53 publications

(38 citation statements)

References 39 publications

(60 reference statements)

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“…Note the characterization of surface-endpoints S1 are applied in some existing thinning algorithms [1,11,16]. Note that the characterization of surface-endpoints S2 is introduced in [15].…”

Section: Examples Of the New 6-subiteration Thinning Algorithmsmentioning

confidence: 99%

“…By adapting the efficient implementation method presented in [16] our algorithms can be well applied in practice: they are capable of extracting skeleton-like features from large 3D shapes within one second on a usual PC.…”

Section: Examples Of the New 6-subiteration Thinning Algorithmsmentioning

confidence: 99%

“…The deletion rules of existing parallel thinning algorithms are generally given by matching templates with specific and "built-in" endpoint characterizations [1,3,8,9,10,11,14,15,16,20] with the exceptions of some 3D fully parallel algorithms [17] and some 3D subfield-based thinning algorithms [12,13]. In this paper, we introduce a general scheme for 6-subiteration 3D parallel thinning that is based on our new sufficient conditions for topology preservation.…”

Section: Introductionmentioning

confidence: 99%

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A Family of Topology–Preserving 3D Parallel 6–Subiteration Thinning Algorithms

Németh

Kardos

Palágyi

2011

Lecture Notes in Computer Science

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Abstract.Thinning is an iterative layer-by-layer erosion until only the skeleton-like shape features of the objects are left. This paper presents a family of new 3D parallel thinning algorithms that are based on our new sufficient conditions for 3D parallel reduction operators to preserve topology. The strategy which is used is called subiteration-based: each iteration step is composed of six parallel reduction operators according to the six main directions in 3D. The major contributions of this paper are: 1) Some new sufficient conditions for topology preserving parallel reductions are introduced. 2) A new 6-subiteration thinning scheme is proposed. Its topological correctness is guaranteed, since its deletion rules are derived from our sufficient conditions for topology preservation.3) The proposed thinning scheme with different characterizations of endpoints yields various new algorithms for extracting centerlines and medial surfaces from 3D binary pictures.

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“…Note the characterization of surface-endpoints S1 are applied in some existing thinning algorithms [1,11,16]. Note that the characterization of surface-endpoints S2 is introduced in [15].…”

Section: Examples Of the New 6-subiteration Thinning Algorithmsmentioning

confidence: 99%

Section: Examples Of the New 6-subiteration Thinning Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Family of Topology–Preserving 3D Parallel 6–Subiteration Thinning Algorithms

Németh

Kardos

Palágyi

2011

Lecture Notes in Computer Science

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“…The recent study of Palágyi [18] shows that a robust (both topology-preserving and maximum thinning) surface-thinning algorithm is possible. It deals with the full 26-adjacent voxels to p, see Figure 14.…”

Section: Thinning In Zmentioning

confidence: 99%

“…Due to the extended neighbor dependency, this procedure, although becoming more complex than its 2D counterpart, still seems manageable. A complete set of 114 structuring elements are suggested in [18]. Details of this algorithm can be found in the original paper.…”

Section: Thinning In Zmentioning

confidence: 99%

Distance Solutions for Medial Axis Transform

Xia

Tucker

2009

Proceedings of the 18th International Meshing Roundtable

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Abstract.A method towards robust and efficient medial axis transform (MAT) of arbitrary domains using distance solutions is presented. The distance field, d, is calculated by solving the hyperbolic-natured Eikonal (or Level Set) equation. The solution is obtained on Cartesian grids. Both the fast-marching method and fast-sweeping method are used to calculate d. Medial axis point clouds are then extracted based on the distance solution via a simple criteria: the Laplacian or the Hessian determinant of d. These point clouds in 2D-pixel and 3D-voxel space are further thinned to curves and surfaces through binary image thinning algorithms. This results in an overall hybrid approach. As an alternative to other methods, the current d−MAT procedure bypasses difficulties that are usually encountered by pure geometric methods (e.g. the Voronoi approach), especially in 3D, and provides better accuracy than pure thinning methods. It is also shown that the d−MAT approach provides the potential to sculpt/control the MAT form for specialized solution purposes. Various examples are given to demonstrate the current approach.

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Three‐dimensional thinning algorithms on graphics processing units and multicore CPUs

Jiménez

Miras

2011

Concurrency and Computation

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Three-dimensional curve skeletons are a very compact representation of three-dimensional objects with many uses and applications in fields such as computer graphics, computer vision, and medical imaging. An important problem is that the calculation of the skeleton is a very time-consuming process. Thinning is a widely used technique for calculating the curve skeleton because of the properties it ensures and the ease of implementation. In this paper, we present parallel versions of a thinning algorithm for efficient implementation in both graphics processing units and multicore CPUs. The parallel programming models used in our implementations are Compute Unified Device Architecture (CUDA) and Open Computing Language (OpenCL). The speedup achieved with the optimized parallel algorithms for the graphics processing unit achieves 106.24x against the CPU single-process version and more than 19x over the CPU multithreaded version.

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A 3D fully parallel surface-thinning algorithm

Cited by 53 publications

References 39 publications

A Family of Topology–Preserving 3D Parallel 6–Subiteration Thinning Algorithms

A Family of Topology–Preserving 3D Parallel 6–Subiteration Thinning Algorithms

Distance Solutions for Medial Axis Transform

Three‐dimensional thinning algorithms on graphics processing units and multicore CPUs

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