Pavement Surface Distress Detection Using Digital Image Processing Techniques

Abstract

Road safety and pavement condition are considered top priorities in our civilized societies, and it’s important that the pavement condition remains in an excellent state for a long time. However, eventually, the pavement will get exposed to different types of distresses as a result of traffic loads, rough environment conditions, soil conditions, and underline subgrade. Therefore, to achieve the required standards for the pavement surface roads in our country and provide the best performance: detection and measurements of distresses extension must be included in maintenance preparation. This paper proposes a technique for crack detection based on digital image processing using a programming language called Matrix Laboratory known as MATLAB. The main target is to estimate the pavement’s length, width, and area by capturing the image using a digital camera with the required precautions and image implementation. Secondly, developing an image pre-processing operation to eliminate environmental interference as much as possible and subsequently use the image thresholding method to separate the pixels within the image into two groups to find the thresholding value for image binarization. The method successfully detects and removes the presence of unwanted objects in an image, even in difficult situations where surfaces are less visible. Verification showed good results with an excellent processing time, which can be considered an indicator of pavement crack parameters.