Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0010-4485(03)00097-6
Title: Modelling cloud data using an adaptive slicing approach
Authors: Wu, Y.F. 
Wong, Y.S. 
Loh, H.T. 
Zhang, Y.F. 
Keywords: Cloud data
Layer-based model
Rapid prototyping
Reverse engineering
Shape-error
Issue Date: Mar-2004
Source: Wu, Y.F.,Wong, Y.S.,Loh, H.T.,Zhang, Y.F. (2004-03). Modelling cloud data using an adaptive slicing approach. CAD Computer Aided Design 36 (3) : 231-240. ScholarBank@NUS Repository. https://doi.org/10.1016/S0010-4485(03)00097-6
Abstract: In reverse engineering, the conventional surface modelling from point cloud data is time-consuming and requires expert modelling skills. One of the innovative modelling methods is to directly slice the point cloud along a direction and generate a layer-based model, which can be used directly for fabrication using rapid prototyping (RP) techniques. However, the main challenge is that the thickness of each layer must be carefully controlled so that each layer will yield the same shape error, which is within the given tolerance bound. In this paper, an adaptive slicing method for modelling point cloud data is presented. It seeks to generate a direct RP model with minimum number of layers based on a given shape error. The method employs an iterative approach to find the maximum allowable thickness for each layer. Issues including multiple loop segmentation in layers, profile curve generation, and data filtering, are discussed. The efficacy of the algorithm is demonstrated by case studies. © 2004 Elsevier Ltd. All rights reserved.
Source Title: CAD Computer Aided Design
URI: http://scholarbank.nus.edu.sg/handle/10635/60806
ISSN: 00104485
DOI: 10.1016/S0010-4485(03)00097-6
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