Graduation Year

2004

Document Type

Dissertation

Degree

Ph.D.

Degree Granting Department

Civil Engineering

Major Professor

Gunaratne, Manjriker.

Keywords

assessment, image, quality, noise, filtering, pavement

Abstract

Manual pavement condition surveys are gradually replaced by more comprehensive automated surveys conducted by multi-function highway evaluation vehicles. Highway evaluation vehicles are generally equipped with laser profiling, land navigation, and imaging sub-systems. The imaging system consists of three cameras; forward-view and side-view digital area-scan cameras for capturing images of traffic signs and right-of-way safety features, and a pavement digital line-scan or area-scan camera for capturing images of the pavement surface. In addition to the 3-laser and accelerometer-based profiling system, these vehicles are also equipped with differential global positioning equipment (DGPS) and an inertial measurement unit (IMU) for cross-slope, curvature and grade measurements.

Digital imaging systems installed in automated highway evaluation vehicles are generally designed on modular basis where subsystems by different manufacturers are assembled to customize the system and fulfill the users' needs while minimizing the cost. In most such cases, manufacturers' specifications for a subsystem would not be reliable with respect to the eventual performance of that subsystem as part of the entire assembly. On the other hand, no guidelines are available for performance evaluation of imaging systems as assemblies of discrete subsystems. Moreover, images acquired by digital cameras can become contaminated by random noise affecting their quality and the ability of identifying important features. These issues have surfaced during the development and testing of the Florida Department of Transportation (FDOT) highway evaluation vehicle.

This first phase of the work involved in this dissertation research concerns the study of basic criteria for evaluation of image quality through measurement of well-defined properties of images such as color reproduction, tone reproduction, detail reproduction, as well as the levels of noise, and optical distortion. Standard and reliable methods that can be adopted for evaluation of the above properties are discussed first. Then, by applying the above evaluation criteria to the imaging systems of the FDOT highway evaluation vehicle, it is shown how the sources of images sub-quality can be recognized and the optimum settings achieved. The second phase of the dissertation research is focused on the investigation of the sources of noise that can affect the digital line-scan distress images.

As a result of this study, a novel technique was developed to filter out noise present in pavement distress images by using intensity measurement obtained from a standard grayscale target. In addition, a detailed experimental study was conducted to investigate the effect of the speed of evaluation and lighting conditions on the accuracy and repeatability of digital line-scan images in representing the actual distress condition of a pavement. The conclusions drawn from the second phase can be used to minimize the effect of noise on digital images of pavement distress and to improve the accuracy of evaluation of pavement cracks based on digital images. Hence the results of this study will certainly enhance the overall efficiency of the automated evaluation of pavement distress and highway features.

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