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Using a dSLR camera with macro LED light, 11 samples containing light and moderately cracked concrete surfaces were imaged with perpendicular and angled illumination. Textural features from gray level co-occurrence matrix statistics were derived, from which 3-6 salient features were selected. Cross validation accuracies were as high as 94% using neural network classifiers, indicating the feasibility of rapid, automatic concrete cracking assessment using COTS digital imaging.
Date of Conference: July 31 2011-Aug. 5 2011