ABSTRACT
Recently, the digital image processing algorithm based crack inspection and identification methods have gained considerable attentions. Yeum and Dyke (2015) proposed a vision-based automated method to detect cracks near bolts on the bridges. Lee et al. (2009) investigated the crack propagation in composite materials in one direction with the aid of digital image correlation technique and high-speed and continuous photographic techniques. Liu et al. (2014) proposed a method for automated surface crack monitoring and assessment of concrete structures based on adaptive digital image processing. Jahanshahi et al. (2011) developed a method to inspect the condition of bridge structures by stitching multiple images and reconstructing local features and comparing with the database created to detect the defections of structures. Halfawy and Hengmeechai (2015) embedded the vision based defection recognition system into the closed circuit television (CCTV) system mounted in the sewer to inspect its defections automatically. Adhikari et al. (2014) presented an approach of automated condition assessment of concrete bridges based on digital image analyses. Koch et al. (2014) presented the current progress and difficulties in computer vision-based detection technique for large scale concrete structures.
