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Robotic three-dimensional imaging system for under-vehicle inspection

[+] Author Affiliations
Sreenivas R. Sukumar

The University of Tennessee, Department of Electrical and Computer Engineering, Imaging, Robotics, and Intelligent Systems Laboratory, Knoxville, Tennessee 37996-2100

David L. Page

The University of Tennessee, Department of Electrical and Computer Engineering, Imaging, Robotics, and Intelligent Systems Laboratory, Knoxville, Tennessee 37996-2100

Andrei V. Gribok

The University of Tennessee, Department of Electrical and Computer Engineering, Imaging, Robotics, and Intelligent Systems Laboratory, Knoxville, Tennessee 37996-2100

Andreas F. Koschan

The University of Tennessee, Department of Electrical and Computer Engineering, Imaging, Robotics, and Intelligent Systems Laboratory, Knoxville, Tennessee 37996-2100

Mongi A. Abidi

The University of Tennessee, Department of Electrical and Computer Engineering, Imaging, Robotics, and Intelligent Systems Laboratory, Knoxville, Tennessee 37996-2100

David J. Gorsich

U.S. Army RDECOM Tank-Automotive Research, Development and Engineering Center, Warren, Michigan 48397-5000

Grant R. Gerhart

U.S. Army RDECOM Tank-Automotive Research, Development and Engineering Center, Warren, Michigan 48397-5000

J. Electron. Imaging. 15(3), 033008 (August 16, 2006). doi:10.1117/1.2238565
History: Received June 24, 2005; Revised December 08, 2005; Accepted January 30, 2006; Published August 16, 2006
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We present our research efforts toward the deployment of 3-D sensing technology to an under-vehicle inspection robot. The 3-D sensing modality provides flexibility with ambient lighting and illumination in addition to the ease of visualization, mobility, and increased confidence toward inspection. We leverage laser-based range-imaging techniques to reconstruct the scene of interest and address various design challenges in the scene modeling pipeline. On these 3-D mesh models, we propose a curvature-based surface feature toward the interpretation of the reconstructed 3-D geometry. The curvature variation measure (CVM) that we define as the entropic measure of curvature quantifies surface complexity indicative of the information present in the surface. We are able to segment the digitized mesh models into smooth patches and represent the automotive scene as a graph network of patches. The CVM at the nodes of the graph describes the surface patch. We demonstrate the descriptiveness of the CVM on manufacturer CAD and laser-scanned models.

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© 2006 SPIE and IS&T

Citation

Sreenivas R. Sukumar ; David L. Page ; Andrei V. Gribok ; Andreas F. Koschan ; Mongi A. Abidi, et al.
"Robotic three-dimensional imaging system for under-vehicle inspection", J. Electron. Imaging. 15(3), 033008 (August 16, 2006). ; http://dx.doi.org/10.1117/1.2238565


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