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Data Fusion and 3D Geometric Modeling from Multi-scale Sensors

  • Dmitry TanskyEmail author
  • Anath Fischer
Part of the Lecture Notes in Production Engineering book series (LNPE)

Abstract

The past several decades have seen major advances in sensor technologies, including surface scanning at multi-scales. While state-of-the-art research focuses on methods for integrating diverse scanned data into a single geometric model for inspection analysis, these methods still cannot handle multi-scale data. This paper proposes a new approach for data fusion from multi-scale sensors by defining two generic frameworks for data fusion: Single-Level Multi-Sensor (SLMS) for multi-scale data merged on one level and Hierarchical Multi-Sensor (HMS) for hierarchically merged multi-scale data. These frameworks are based on state-of-the-art generic frameworks and use the properties of multi-scale sensors properties. The feasibility of the proposed approach is demonstrated on 2.5D surfaces scanned by CMM touch probes and laser scanners and on 3D multi-scale synthetic data from CAD models.

Keywords

data fusion multi-sensors multi-scale inspection analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Faculty of Mechanical EngineeringTechnionHaifaIsrael

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