Improved numerical method for determination of pavement mean texture depth from 3-dimensional digital image

Abstract

The conventional manual sand-patch method of mean texture depth (MTD) measurement is unsuitable for network level pavement condition monitoring. Relying on 2-D mean linear profile depth (MPD) to estimate 3-D MTD is also unsuitable because MTD-MPD regression relationship varies from one pavement mix type to another. This problem of network level MTD measurements and monitoring can be overcome if MTD could be numerically determined from 3-D digital laser images. All the numerical MTD determination methods proposed by researchers in recent years made a common invalid assumption that the MTD top surface was defined by the high texture peaks of the test surface. This study presents evidence to show that the top surface defining MTD actually lies below the highest peaks of the test surface. Next, applying the concept of planation surface, a novel numerical procedure is proposed to identify a reference surface for MTD calculation by means of a second-derivative plot of peak-height percentiles. The validity of the proposed method was verified experimentally with measured MTD values of both laboratory fabricated specimens and in-service pavements. For four different surface course materials, the errors in the predicted MTD values range from 0.20 to 7.31 %. The proposed method produced improved accuracy in MTD predictions compared with the existing methods which were based on incorrectly assumed MTD top surfaces.