Open AccessPavement Raveling Detection and Measurement from Synchronized Intensity and Range Images
Author(s) -
Senthan Mathavan,
Mujib Rahman,
Martyn Stonecliffe-Jones,
Khurram Kamal
Publication year - 2014
Publication title -
transportation research record
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.624
H-Index - 119
eISSN - 2169-4052
pISSN - 0361-1981
DOI - 10.3141/2457-01
Subject(s) - pothole (geology) , asphalt , computer vision , texture (cosmology) , range (aeronautics) , computer science , artificial intelligence , engineering , geology , materials science , image (mathematics) , petrology , composite material , aerospace engineering
Raveling on asphalt surfaces is a loss of fine and coarse aggregates from the asphalt matrix. The severity of raveling can be an indicator of the state of pavements, as excessive raveling not only reduces the ride quality but eventually leads to pothole formation or cracking. Hence, raveling must be detected and quantified. In this study and for the first time, raveling was quantified from a combination of two- and three-dimensional images. First, a texture descriptor method called Laws’ texture energy measure was used in conjunction with Gabor filters and other morphological operations to distinguish road areas. Then, digital signal processing techniques were used to detect and to quantify raveling. Hundreds of images captured by an automated pavement surveying system were used to test and to show the promise of the proposed algorithm.