Bend Detection of Bridge Chords in UAV Images via Region-Based Deep Semantic Segmentation Network

Vision-based techniques are gradually being applied to civil engineering fields by aiding human resources to inspect and assess the condition of structures. This paper presents a vision-based inspection system to detect bends of the bridge chords in UAV images. The main parts of this paper firstly present a novel region proposal algorithm to localize bridge chord bends without distinct boundaries and then present a fusion-based deep semantic segmentation network that improves the detection performance by fusing spatial information from neighborhood. The proposed system achieves approximate 0.7762 Mean IOU and 0.6424 BF Score on the field dataset, which outperforms the other state-of-the-art systems.