Scanned Three-Dimensional Model Matching and Comparison Algorithms for Manufacturing Applications

[+] Author and Article Information
Vahram Avagyan, Armen Zakarian

Department of Industrial and Manufacturing Systems Engineering,  University of Michigan-Dearborn, Dearborn, MI 48128

Pravansu Mohanty

Department of Mechanical Engineering,  University of Michigan-Dearborn, Dearborn, MI 48128

J. Manuf. Sci. Eng 129(1), 190-201 (Jul 18, 2006) (12 pages) doi:10.1115/1.2375139 History: Received July 29, 2005; Revised July 18, 2006

In recent years the increased use of 3D scanning hardware has introduced a new type of data to the design and manufacturing field. In many design and manufacturing applications (e.g., part refurbishing or remanufacturing) a scanned 3D model may be provided as an input to a shape matching system to search the database for related or identical models with the purpose of extracting useful information. The introduction of scanned 3D models restricts the use of the CAD-based 3D model search and comparison methods due to significant differences in model representations. The CAD models provide structured and high-level representation of the part features, whereas the scanned 3D models usually come in a polygonal mesh representation, which does not directly reveal engineering features of the part. These differences require new algorithms for comparing the shapes of scanned 3D models, ones that are robust against different scanning technologies and can be adjusted to work with different representations of the models. In this paper, a new approach and algorithms for scanned 3D shape matching and comparison are presented. Given the scanned 3D model as an input the approach first uses general-purpose shape matching methods to identify a small list of likely matches (i.e., candidate models) for more detailed shape comparison. To perform detailed comparison of the shapes each candidate model is geometrically adjusted (i.e., rotated and translated) with the input using one of two new viewpoint algorithms developed in this paper. Once the candidate models are adjusted they are compared to the input to identify the similarities and differences between their shapes. To accomplish this task a new 3D shape matching algorithm is developed. The relevance of the methodology developed in this paper is illustrated with the application of scanned 3D shape matching and comparison algorithms in rapid manufacturing of broken parts.

Copyright © 2007 by American Society of Mechanical Engineers
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Figure 7

The broken part and its original used in the first illustrative example

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Figure 8

Results of the statistical similarity estimation approach

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Figure 9

Animation snapshot from the sphere viewpoint algorithm

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Figure 10

Final results obtained from the shape comparison algorithm

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Figure 11

Final results obtained from the shape comparison algorithm shows: (a) broken section∕volume that needs to be repaired with the SFF technique and (b) layered representation of a broken part for rapid remanufacturing

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Figure 1

Phases of the 3D model matching methodology

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Figure 2

Two candidate models with the different placement and orientation

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Figure 3

Similar sections A and B of candidate models in Fig. 2 represented with different polygons

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Figure 4

Settings of the sphere viewpoint algorithm

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Figure 5

Settings of the cylinder viewpoint algorithm

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Figure 6

Tagged point structure



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