Contour curve reconstruction from cloud data for rapid prototyping F. Javidrad n , A.R. Pourmoayed Center for Postgraduate Studies, Aeronautical University of Science and Technology, Sought Mehrabad, Shamshiri st., 13846-73411 Teharn, Iran article info Article history: Received 12 March 2010 Received in revised form 9 July 2010 Accepted 23 August 2010 Keywords: Reverse engineering Contour curve Rapid prototyping Interval B-spline abstract In this study, a method for generation of sectional contour curves directly from cloud point data is given. This method computes contour curves for rapid prototyping model generation via adaptive slicing, data points reducing and B-spline curve fitting. In this approach, first a cloud point data set is segmented along the component building direction to a number of layers. The points are projected to the mid-plane of the layer to form a 2-dimensional (2D) band of scattered points. These points are then utilized to construct a boundary curve. A number of points are picked up along the band and a B-spline curve is fitted. Then points are selected on the B-spline curve based on its discrete curvature. These are the points used as centers for generation of circles with a user-define radius to capture a piece of the scattered band. The geometric center of the points lying within these circles is treated as a control point for a B-spline curve fitting that represents a boundary contour curve. The advantage of this method is simplicity and insensitivity to common small inaccuracies. Two experimental results are included to demonstrate the effectiveness and applicability of the proposed method. & 2010 Elsevier Ltd. All rights reserved. 1. Introduction Reverse engineering (RE) is a conventional design tool for producing a computerized model of an existing object based on point data acquired from the object surface. In traditional RE technology, first a designed model or mock-up is sampled using either contact or non-contact scanning devices. Then sampled data are transferred to a CAD environment for computerized representation and further design work. Various scanning tech- niques are now commercially available. Contact type devices are generally more accurate than non-contact devices, although they are often much slower in data acquision. In recent years, the accuracy of the non-contact types of devices has improved significantly. Optical non-contact scanning such as laser scanning is a commercial technology that could be utilized to produce a large cloud data set in a short time. Once a cloud point data set is produced, then it should be processed to extract a CAD model. In this process, extraction of useful data points from the cloud data is the first action. This procedure usually called segmentation. In this procedure, the acquired point cloud is divided into several smooth regions for surface or curve fitting purposes. Segmentation procedure to develop a fully automated method is now a challenging research area including many disciplines. This serves as a motivation for exploring the possibility of finding a procedure used for creation of a CAD model directly from the cloud point data. Rapid prototyping (RP) is a growing fabrication method in which a copy of the designed component is produced layer by layer. RP is currently a manufacturing technique for creating models of complex physical objects in a shorter time than those of more traditional prototype fabrication methods [1]. RP involves processes that are principally different from other traditional material removing methods. In RP method, adding or solidifying materials layer by layer generates a volume of the materials. Since RP process requires sectional contours perpendicular to an axis direction, the CAD model or data points must be sectioned in the form of thin layers from which sectional contour curves are determined. These contours actually define RP machine tool paths. To achieve an accurate prototype, these contour curves must be determined as accurately as possible. In this study, an algorithm is introduced to generate sectional curves directly from data points. This algorithm computes sectional curves via slicing, data point reducing and curve fitting. In this algorithm, there is no limitation in cloud data density and distribution. Nevertheless, the captured data by most of non- contact type devices is too dense, randomly distributed and partially overlapped. Therefore, generation of a CAD model from such a data can be a laborious task [2]. Although the proposed algorithm is not a fully automatic process, it is simple and accurate enough if the user-defined parameters properly selected. 2. Related works Transforming a point cloud data set to a CAD or a prototype model generally classified based on three approaches: triangular mesh generation, segmentation and fitting and direct slicing. Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/rcim Robotics and Computer-Integrated Manufacturing 0736-5845/$ - see front matter & 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.rcim.2010.08.008 n Correponding author. Tel.: +98 21 88570541. E-mail address: f_javidrad@yahoo.com (F. Javidrad). Robotics and Computer-Integrated Manufacturing 27 (2011) 397–404