Automatic crack detection from pavement images using fuzzy thresholding

Abstract

These last decades have seen the application of automatic inspection in many fields thanks to advanced vision sensors and image analysis methods. However, the difficult nature of pavement images, the small size of defects (cracks) lead to the fact that inspection in this area is done mostly manually. Each year in Tunisia, the operator must view images of thousands of kilometers of roads to detect these degradations. This method is expensive, slow and has a rather subjective result. In this paper, we present a method for automated crack detection. The proposed approach consists of detection of defects. For crack detection, we have applied the method Fuzzy Classification Method (FCM) thresholding. This methodology has been implemented in a Matlab prototype, trained and tested on 330 real pavement images. The results show that this method can detect a crack in pavement images with reasonable accuracy.