Feature-Driven Viewpoint Placement for Model-Based Surface Inspection
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ORIGINAL PAPER
Feature-Driven Viewpoint Placement for Model-Based Surface Inspection Dennis Mosbach1,2
· Petra Gospodneti´c1,2 · Markus Rauhut2 · Bernd Hamann3 · Hans Hagen1
Received: 25 July 2019 / Revised: 10 July 2020 / Accepted: 20 August 2020 © The Author(s) 2020
Abstract The goal of visual surface inspection is to analyze an object’s surface and detect defects by looking at it from different angles. Developments over the past years have made it possible to partially automate this process. Inspection systems use robots to move cameras and obtain pictures that are evaluated by image processing algorithms. Setting up these systems or adapting them to new models is primarily done manually. A key challenge is to define camera viewpoints from which the images are taken. The number of viewpoints should be as low as possible while still guaranteeing an inspection of the desired quality. System engineers define and evaluate configurations that are improved based on a time-consuming trial-and-error process leading to a sufficient, but not necessarily optimal, configuration. With the availability of 3D surface models defined by triangular meshes, this step can be done virtually. This paper presents a new scalable approach to determine a small number of well-placed camera viewpoints for optical surface inspection planning. The initial model is approximated by B-spline surfaces. A set of geometric feature functionals is defined and used for an adaptive, non-uniform surface sampling that is sparse in geometrically low-complexity areas and dense in regions of higher complexity. The presented approach is applicable to solid objects with a given 3D surface model. It makes camera viewpoint generation independent of the resolution of the triangle mesh, and it improves previous results considering number of viewpoints and their relevance. Keywords View planning · Object space exploration · Inspection automation · B-spline surface · Model-based planning
1 Introduction With the abundance of various sensing methods, almost every produced object undergoes a quality assurance pro-
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Dennis Mosbach [email protected] Petra Gospodneti´c [email protected] Markus Rauhut [email protected] Bernd Hamann [email protected] Hans Hagen [email protected]
1
Computer Graphics and HCI Group, University of Kaiserslautern, 67663 Kaiserslautern, Germany
2
Image Processing Department, Fraunhofer ITWM, 67663 Kaiserslautern, Germany
3
Department of Computer Science, University of California, Davis, CA 95616, USA
cess. Because of their availability and application versatility, optical sensors are commonly utilized, both as a support and a primary sensing device. When it comes to surface quality inspection, they are especially useful as there are many advanced machine vision tools available (e.g., [3,10,15]). Moreover, they enable the possibility of inspecting both optical and spatial properties of the object. Over the years, significant effort has been put into inspection process automati
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