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Unsupervised Defect Detection for Autonomous Pavement Condition Assessment

Current pavement condition assessment procedures are extensively time consuming, laborious, qualitative, and costly. In this study, we have developed a data analysis tool that processes the data collected by an inexpensive RGB-D sensor to autonomously detect, localize and, most importantly, quantify a variety of defects, including patching, cracks, and potholes, in pavements.

Related Publication

Mohammad R. Jahanshahi and Sami F. Masri, (2013), "Parametric performance evaluation of wavelet-based corrosion detection algorithms for condition assessment of civil infrastructure systems," Journal of Computing in Civil Engineering, American Society of Civil Engineers (ASCE), Vol. 27, No. 4, July 2013, 345-357.