Graduation Year

2004

Document Type

Thesis

Degree

M.S.C.E.

Degree Granting Department

Civil Engineering

Major Professor

Manjriker Gunaratne, Ph.D.

Committee Member

Alaa Ashmawy, Ph.D.

Committee Member

Ram Pendyala, Ph.D.

Keywords

automated pavement distress data collection, pavement distress imaging systems, pavement surface distress, pavement cracking, imaging quality

Abstract

The use of high technology in common daily tasks is boarding all areas of civil engineering; pavement evaluation is not the exception. Accordingly, current pavement imaging systems have been able to collect images at highway speeds and with the use of proper software, this digital information can be translated into pavement distress reports in which all distresses are classified and presented by their type, extent, severity, and location. However, a number of issues regarding the quality of pavement images and the appropriate conditions to acquire them, remain to be addressed. These issues surfaced during the development of a pavement evaluation vehicle for the Florida Department of Transportation (FDOT).

The work involved in this thesis proposes basic criteria to evaluate the performance of pavement imaging systems. Mainly four parameters (1) spatial resolution, (2) brightness resolution, (3) optical distortion, and (4) signal to noise ratio, have been identified to assess the quality of a pavement imaging system. First, each of the four parameters is studied in detail in USF's Visual Imaging Laboratory to formulate relevant criteria that can be used to evaluate imaging systems. Then, the developed criteria are used to evaluate the FDOT Survey Vehicle's pavement imaging system. The evaluation speed does not seem to have any significant influence on the spatial resolution, brightness resolution and signal to noise ratio. Little or no optical distortion was observed on the images on wheel paths. Limitations of the imaging system were also determined in terms of the brightness resolution and noise. The conclusions drawn from this study can be used to (1) enhance pavement imaging systems and (2) setup appropriate guidelines to perform automated distress surveys, under varying lighting conditions and speeds to obtain good quality images.

Download

Share

COinS