Development of new automated crack measurement algorithm using laser images of pavement surface

Over the years, many Automated Image Collection Systems (AICS) have been developed to capture pavement images. The cameras used by most of the AICS are based on Charge-Coupled Device (CCD) image sensors where visible ray is projected. However, the quality of the images captured by the CCD cameras was limited by the inconsistent illumination and shadows caused by sunlight. To enhance the CCD image quality, a high-power artificial lighting system has been used, which required a complicated strobe lighting system and a significant power source. Recently, Laser Road Imaging System (LRIS) was introduced which would capture laser images such that there is no shadow. The main purpose of this study is to discuss an implementation of LRIS that includes a LRIS mounting system, pavement image acquisition software and crack analysis software. The images captured using the LRIS were very sharp without a shadow but due to a high contrast of pavement surface it resulted in a higher amount of noise. Therefore, a new automated image processing algorithm is developed to suppress the background noises while enhancing crack images based on the unique characteristics of the laser image. Based on the limited set of laser images, the proposed algorithm is more accurate than the thresholding method with a relative precision up to 83.1%.