Efficient Algorithms for Automatic Detection of Cracks on a Concrete Bridge

Abstract

In the bridge inspection, the information of cracks is important to maintain a bridge. Therefore, automatic crack detection is highly desirable for efficiency and objectivity of crack assessment. However, in general, it is very difficult to detect cracks automatically from noisy concrete surfaces. In this paper, we propose a machine vision system for automatic inspection of bridges. The proposed machine vision system can detect cracks in real time, and it has some utility functions for supervised manipulation. The performance of the proposed system has been evaluated with 100 noisy images. In terms of accuracy in detecting cracks, experimental results show that the proposed method is superior to the conventional methods for detecting cracks.