Water leakage image recognition of shield tunnel via learning deep feature representation

Abstract

With the development of urban metro, the research on structural diseases of shield tunnels has been becoming a hot research topic, especially the leakage water diseases. Deep learning-based algorithms have shown impressive performance in image processing domain, such as image classification, image recognition or image retrieval. In this paper, we propose a novel image recognition algorithm for water leakage diseases of shield tunnels based on deep learning algorithm. Water leakage images are classified into six categories, each of which are extracted deep representation for image recognition. We compare our method with Otsu algorithm (OA), Region Growing Algorithm (RGA), and Watershed Algorithm (WA) to show the effectiveness of our proposed method.