3D Imaging based pavement texture evaluation

Abstract

ABSTRACT Pavement texture is an important surface characteristic for safety evaluation. Through a series of laboratory and field testing, this study presents an automatic non-contact method using high resolution 3D images for accurate and efficient pavement texture evaluation. Firstly, a 3D laser device was applied to capture pavement texture. Subsequently, the 3D texture images were denoised using image processing methods. Then, the 3D seed filling algorithm was developed to calculate mean texture depth (MTD) and mean profile depth (MPD). The computed MTD and MPD values from 3D images showed a good correlation with results of sand patch testing and high repeatability. Further, through the follow-up field testing, the proposed method using 3D images showed better performance in texture evaluation than the 2D texture profiler or sand patch testing. The results indicate it is accurate and efficient to evaluate pavement texture using high resolution 3D images in a non-contact and automatic manner.