Segmentation of the Measured Point Data in Reverse Engineering

Kim, Ho-Chan; Hur, Sung-Min; Lee, S.-H.

doi:10.1007/s001700200193

Cited by 11 publications

(6 citation statements)

References 10 publications

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“…This technology enables us to create the computer digital model of the object either with no design data or when there are many design changes [22]. In reverse engineering real parts are transformed into engineering models and concepts, while conventional engineering transforms engineering concepts and models into real parts.…”

Section: Reverse Engineering Of Large Objectsmentioning

confidence: 99%

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Virtual modelling through human vision sense

Alves

Bartolo

2007

Int J Interact Des Manuf

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The restoration/renovation of historic buildings has become an important facet of the construction industry, which can generate large economic benefits, drawn from the increased commercial value of these buildings and its surrounding area in terms of tourism and investment, apart from other non-priced benefits associated with user satisfaction. In this context, the rapid generation of tridimensional computer models from existent large objects like historic buildings can be particularly important either for building re-use, virtual museums or others patrimonial applications. This paper proposes a new biologically based computer tool, called Bio-CAD that mimics the human vision process. This system was specifically designed for the rapid and accurate generation of 3D computer models from existing large objects and can be integrated with other computer-based technologies. Two case studies were chosen to validate the system and to demonstrate its integration with rapid prototyping and Haptic CAD systems.

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Section: Reverse Engineering Of Large Objectsmentioning

confidence: 99%

“…Finally, the STL file is sliced into a set of slices (Figs. 21,22,23,24) and a physical model produced using a commercial available rapid prototyping system (Figs. 25, 26).…”

Section: Case Studymentioning

confidence: 99%

Virtual modelling through human vision sense

Alves

Bartolo

2007

Int J Interact Des Manuf

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“…Their method was essentially suitable for the meshes from the CAD models, but not from 3D scanning. Kim et al [11] divided the triangular meshes into regular ones and noisy ones and employed a criterion in terms of the angle between two neighboring meshes to separate the regular meshes. The curvatures evaluated on the edges were employed to isolate the noisy data too.…”

Section: Introductionmentioning

confidence: 99%

Development of feature segmentation algorithms for quadratic surfaces

Lai¹,

Chang²,

Lai³

2009

Advances in Engineering Software

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“…For instance, splitting an image or a 3D object in smaller parts is very useful to perform high-level recognition (Kokkinos and Maragos, 2009;Ferrari et al, 2006), reverse engineering (Courtial and Vezzetti, 2008;Kim et al, 2002), parts retrieval (Antini et al, 2005) and even tracking (Colombari et al, 2007). Of course, the expected outcome of a segmentation procedure is different depending on the intended use of the resulting parts.…”

Section: Introductionmentioning

confidence: 99%

A graph-based technique for semi-supervised segmentation of 3D surfaces

Bergamasco

Albarelli

Torsello

2012

Pattern Recognition Letters

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a b s t r a c tA wide range of cheap and simple to use 3D scanning devices has recently been introduced in the market. These tools are no longer addressed to research labs and highly skilled professionals, but rather, they are mostly designed to allow inexperienced users to acquire surfaces and whole objects easily and independently. In this scenario, the demand for automatic or semi-automatic algorithms for 3D data processing is increasing. In this paper we address the task of segmenting the acquired surfaces into perceptually relevant parts. Such a problem is well known to be ill-defined both for 2D images and 3D objects, as even with a perfect understanding of the scene, many different and incompatible semantic or syntactic segmentations can exist together. For this reason recent years have seen a great research effort into semi-supervised approaches, that can make use of small bits of information provided by the user to attain better accuracy. We propose a semi-supervised procedure that exploits an initial set of seeds selected by the user. In our framework segmentation happens by propagating part labels over a weighted graph representation of the surface directly derived from its triangulated mesh. The assignment of each element is driven by a greedy approach that accounts for the curvature between adjacent triangles. The proposed technique does not require to perform edge detection or to fit parametrized surfaces and its implementation is very straightforward. Still, despite its simplicity, tests made on a standard database of scanned 3D objects show its effectiveness even with moderate user supervision.

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Segmentation of the Measured Point Data in Reverse Engineering

Cited by 11 publications

References 10 publications

Virtual modelling through human vision sense

Virtual modelling through human vision sense

Development of feature segmentation algorithms for quadratic surfaces

A graph-based technique for semi-supervised segmentation of 3D surfaces

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