Journal
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
Volume 25, Issue 8, Pages 572-580Publisher
WILEY
DOI: 10.1111/j.1467-8667.2010.00674.x
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Funding
- Michigan Ohio University Transportation Center (MIOH-UTC), U.S. Department of Transportation
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This article presents a Beamlet transform-based approach to automatically detect and classify pavement cracks in digital images. The proposed method uses a pavement distress image enhancement algorithm to correct the nonuniform background illumination by calculating the multiplicative factors that eliminate the background lighting variation. To extract linear features such as surface cracks from the pavement images, the image is partitioned into small windows and a Beamlet transform-based algorithm is applied. The crack segments are then linked together and classified into four types: vertical, horizontal, transversal, and block. Simulation results show that the method is effective and robust in the extraction of cracks on a variety of pavement images.
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