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Proceedings Paper

ESARR: enhanced situational awareness via road sign recognition
Author(s): V. E. Perlin; D. B. Johnson; M. M. Rohde; R. M. Lupa; G. Fiorani; S. Mohammad
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Paper Abstract

The enhanced situational awareness via road sign recognition (ESARR) system provides vehicle position estimates in the absence of GPS signal via automated processing of roadway fiducials (primarily directional road signs). Sign images are detected and extracted from vehicle-mounted camera system, and preprocessed and read via a custom optical character recognition (OCR) system specifically designed to cope with low quality input imagery. Vehicle motion and 3D scene geometry estimation enables efficient and robust sign detection with low false alarm rates. Multi-level text processing coupled with GIS database validation enables effective interpretation even of extremely low resolution low contrast sign images. In this paper, ESARR development progress will be reported on, including the design and architecture, image processing framework, localization methodologies, and results to date. Highlights of the real-time vehicle-based directional road-sign detection and interpretation system will be described along with the challenges and progress in overcoming them.

Paper Details

Date Published: 8 May 2010
PDF: 13 pages
Proc. SPIE 7692, Unmanned Systems Technology XII, 76920G (8 May 2010); doi: 10.1117/12.850256
Show Author Affiliations
V. E. Perlin, Quantum Signal LLC (United States)
D. B. Johnson, Quantum Signal LLC (United States)
M. M. Rohde, Quantum Signal LLC (United States)
R. M. Lupa, Quantum Signal LLC (United States)
G. Fiorani, U.S. Army Tank-Automotive Research, Development and Engineering Ctr. (United States)
S. Mohammad, U.S. Army Tank-Automotive Research, Development and Engineering Ctr. (United States)


Published in SPIE Proceedings Vol. 7692:
Unmanned Systems Technology XII
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

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