Characterization of pavement surface texture using photometric stereo techniques.

摘要

The objective of the thesis is to reconstruct the three-dimensional shape of the pavement surface texture from its intensity images. The thesis is concerned with the recovery of pavement surface texture using photometric stereo techniques. A four-source photometric stereo system and associated software to eliminate specular and shadow contributions is developed. Laboratory and field testing is performed to characterize pavement surfaces and correlate different parameters to potentially predict the noise and friction caused by the interaction of tires and pavement.The digital camera captures all images under manual exposure mode where illumination, zoom, focus, shutter speed, aperture and exposure are set to fixed values so that the changes in image intensities are independent of camera settings. The scene is isolated from ambient lights so that the changes in pixel intensities are caused only by surface orientation and reflectance properties. The apparatus must be positioned on the pavement surface for the duration required to capture four images of the surface illuminated from four angles.The four-source photometric stereo system is used for the purpose of overcoming specular distortion and shadow effects. While three light sources are sufficient to recover surface heights, the fourth source provides redundancy and it is used to detect and correct the specular and shadow effects. In this case, the fourth source can be used to recover the surface heights. In the same manner, a shadow appears in one of the three images when an object blocks the incident rays from reaching a certain area. Images with high specularity or shadowing contributions are excluded from the surface recovery procedure.An image processing algorithm is developed for computing surface orientations from image intensities. The ability of the prototype systems to detect a specular effect is assessed by testing synthetic and real surfaces. A known dimensional sphere with/without a specular surface is tested to validate the algorithm. Results show that the system successfully detects a specular contribution. After eliminating specular and shadow contributions, the surface heights are recovered by integrating the surface orientation using global integration. The algorithm also computes surface texture indicators: the mean profile depth and the root mean square roughness.Two prototypes of four-source photometric stereo system are presented. In the first prototype, a digital still camera and four light sources are mounted in a retractable frame to allow height and angle adjustment of the light sources. Each light source is mounted at the center of one of the frame sides so that the sample is illuminated from four azimuth angles: tau = 0°, 90°, 180° and 270°. The entire system is enclosed in a covered box that isolates the sample from the ambient light.Finally, two types of field experiments are conducted using a second prototype (PhotoTexture 2.0) to show the possible applications of PhotoTexture. An airport runway has been tested to examine the relationship between friction and the proposed three-dimensional texture indicators. Also, a tollway has been tested to evaluate the ability of the system to detect texturing grooves. Results show that the photometric stereo system is a promising technique that can be used to improve the understanding of pavement surface characteristics and their relationship with tire/pavement noise and friction. (Abstract shortened by UMI.)