Color Image-Based Defect Detection Method for Bridge Coating Assessment

This paper presents a highly efficient method for recognizing the existence of bridge coating rust defects by using color image processing. The detection of defects on steel bridge surfaces during the operation and maintenance of bridge structures is important to ensure the safety and reliability of them. More advanced techniques such as digital image processing have been studied for better monitoring and detection as existing infrastructure systems are aged and deteriorated rapidly. Recently, image-based defect recognition and assessment methods have gained considerable attention in the civil engineering domain due to their accuracy, speed, and lower cost. The proposed method in this paper is a fast decision-making system by utilizing color image processing. It was developed by processing original bridge coating images to generate color values and calculating eigenvalues from each digitized image. The values from two different groups, a defective group and a non-defective group, are compared each other to figure out the feasibility of this approach. Finally, an automated defect recognition method is presented and tested with more images. This method can be used to make a decision whether a given digitized image contains defects.