Detection of Pavement Distress and its Types using Fuzzy C Means Algorithm

Abstract: Pavements are broad spectrum of traffic levels, from two-lane rural routes to multilane interstate highways. It needs reformatory measures to restore safety. The common distresses on pavements are cracks, rutting, Potholes and some distresses. It causes the more accidents because of bad Pavement design. In this paper two steps are involved. The first step deploys the image enhancement that helps to enhance the image quality. Histogram Equalization is the one of the technique in image enhancement. That acts as a graphical representation of the digital image. The second step deploys Image clustering is a high-level description of image content FCM is one of the clustering technique and it separate the data into number of partitions. In this paper FCM is used to determine the pavement cracks. Using Otsu thresholding finds the distress types and lastly finds its severity level. Finally the performance parameter shows it gives a better result to identify the distress types and its level.

Keywords: Histogram Equalization, FCM, Otsu Thresholding, Crack Types.