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Journal of Electronic Imaging

Enhanced adaptive filter-bank-based automated pavement crack detection and segmentation system
Author(s): Clyde A. Lettsome; Yi-Chang J. Tsai; Vivek Kaul
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Paper Abstract

We incorporate, evaluate, and assess the feasibility of using filter banks in automated pavement distress systems from a system level. We integrate a novel filter-bank-based distress segmentation method, which, unlike previously researched methods, does not depend on highpass data. In addition, we incorporate the standard Said Pearlman set partitioning in hierarchical trees compression coder into the automated pavement distress system, which is a first in this area of research. A third contribution of the research is a statistical detection algorithm that assists in overall system performance. Preliminary testing using images provided by the Georgia Department of Transportation demonstrate the promise of the proposed method.

Paper Details

Date Published: 15 October 2012
PDF: 12 pages
J. Electron. Imag. 21(4) 043008 doi: 10.1117/1.JEI.21.4.043008
Published in: Journal of Electronic Imaging Volume 21, Issue 4
Show Author Affiliations
Clyde A. Lettsome, Georgia Institute of Technology (United States)
Yi-Chang J. Tsai, Georgia Institute of Technology (United States)
Vivek Kaul, Georgia Institute of Technology (United States)

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