ANALYSIS ON IMPROVEMENT OF RESOLUTION AND ACCURACY OF AUTOMATIC CRACK DETECTION USING AVERAGE SHIFT MESH

Abstract

It is obligatory to carry out regular visual inspections once every 5 years for aging road bridges. However, it is difficult to carry out inspections with the same quality in the future due to the problems of lack of financial resources, human resources, and technical capabilities in the inspection by visual inspection. Under such circumstances, it is expected that the inspection work will be made more efficient by the automatic damage detection technology using images. In this research, we develop a technique to assist crack detection, which is one of the inspection items, by using image recognition. The images of a wide range of concrete structures taken by a high-resolution camera were mesh-divided into multiple images, and the presence or absence of cracks was determined by an image classifier created by CNN. In addition, by combining the results of moving the positions of mesh division and taking the average value (Average Shift Mesh), the detection accuracy of the cracked portion and the resolution of the output result were improved.