Abstract
This research examined pavement video images collected through application of video imaging system. A low-cost pavement imaging system using video technique was developed. To collect pavement video images, a field test was performed by the developed system. As a result of the video test runs, seven test loops were selected for further image analysis. The collected video images were processed by digital image processing to evaluate pavement condition. The calculated crack index values were analyzed by statistical technique to analyze repeatability of images and to identify significant variables. ANOVA tests for each seven-test loop showed that there was poor repeatability for AC and PCC images. The variable effects were tested using general linear model analysis. As a result of analysis, the significant variables for AC and PCC pavement images were identified.
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