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Cracks are among the earliest indicators of deterioration in concrete structures. Early automatic detection of these cracks can significantly extend the lifespan of critical infrastructures, such as bridges, buildings, and tunnels, while…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Said Harb , Pedro Achanccaray , Mehdi Maboudi , Markus Gerke

Cracks play a crucial role in assessing the safety and durability of manufactured buildings. However, the long and sharp topological features and complex background of cracks make the task of crack segmentation extremely challenging. In…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Huaqi Tao , Bingxi Liu , Jinqiang Cui , Hong Zhang

For structural health monitoring, continuous and automatic crack detection has been a challenging problem. This study is conducted to propose a framework of automatic crack segmentation from high-resolution images containing crack…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Jiawei Zhang , Jun Li , Reachsak Ly , Yunyi Liu , Jiangpeng Shu

Large-scale foundation models have become the mainstream deep learning method, while in civil engineering, the scale of AI models is strictly limited. In this work, a vision foundation model is introduced for crack segmentation. Two…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Kang Ge , Chen Wang , Yutao Guo , Yansong Tang , Zhenzhong Hu , Hongbing Chen

Structural crack detection is a critical task for public safety as it helps in preventing potential structural failures that could endanger lives. Manual detection by inexperienced personnel can be slow, inconsistent, and prone to human…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Subhasis Dasgupta , Jaydip Sen , Tuhina Halder

Bridges are an essential part of the transportation infrastructure and need to be monitored periodically. Visual inspections by dedicated teams have been one of the primary tools in structural health monitoring (SHM) of bridge structures.…

Computer Vision and Pattern Recognition · Computer Science 2019-05-24 Seyed Omid Sajedi , Xiao Liang

Pavement crack detection has long depended on costly and time-intensive pixel-level annotations, which limit its scalability for large-scale infrastructure monitoring. To overcome this barrier, this paper examines the feasibility of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Blessing Agyei Kyem , Joshua Kofi Asamoah , Eugene Denteh , Andrews Danyo , Armstrong Aboah

Automated surface-anomaly detection using machine learning has become an interesting and promising area of research, with a very high and direct impact on the application domain of visual inspection. Deep-learning methods have become the…

Computer Vision and Pattern Recognition · Computer Science 2019-06-12 Domen Tabernik , Samo Šela , Jure Skvarč , Danijel Skočaj

Crack is one of the most common road distresses which may pose road safety hazards. Generally, crack detection is performed by either certified inspectors or structural engineers. This task is, however, time-consuming, subjective and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-19 Rui Fan , Mohammud Junaid Bocus , Yilong Zhu , Jianhao Jiao , Li Wang , Fulong Ma , Shanshan Cheng , Ming Liu

Crack detection plays a pivotal role in the maintenance and safety of infrastructure, including roads, bridges, and buildings, as timely identification of structural damage can prevent accidents and reduce costly repairs. Traditionally,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Feng Ding

The detection of cracks is a crucial task in monitoring structural health and ensuring structural safety. The manual process of crack detection is time-consuming and subjective to the inspectors. Several researchers have tried tackling this…

Computer Vision and Pattern Recognition · Computer Science 2022-08-30 Shreyas Kulkarni , Shreyas Singh , Dhananjay Balakrishnan , Siddharth Sharma , Saipraneeth Devunuri , Sai Chowdeswara Rao Korlapati

Structural Health Monitoring (SHM) is a sustainable and essential approach for infrastructure maintenance, enabling the early detection of structural defects. Leveraging computer vision (CV) methods for automated infrastructure monitoring…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Yingchu Wang , Ji He , Shijie Yu

In practical applications, effectively segmenting cracks in large-scale computed tomography (CT) images holds significant importance for understanding the structural integrity of materials. Classical image-processing techniques and modern…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Vitalii Makogin , Duc Nguyen , Evgeny Spodarev

Automatic detection of cracks in concrete surfaces based on image processing is a clear trend in modern civil engineering applications. Most infrastructure is made of concrete and cracks reveal degradation of the structural integrity of the…

Image and Video Processing · Electrical Eng. & Systems 2021-06-11 Diego Frias , José Hidalgo

The traditional SegNet architecture commonly encounters significant information loss during the sampling process, which detrimentally affects its accuracy in image semantic segmentation tasks. To counter this challenge, we introduce an…

Image and Video Processing · Electrical Eng. & Systems 2024-06-05 Zijun Gao , Qi Wang , Taiyuan Mei , Xiaohan Cheng , Yun Zi , Haowei Yang

Automatic crack detection and segmentation play a significant role in the whole system of unmanned aerial vehicle inspections. In this paper, we have implemented a deep learning framework for crack detection based on classical network…

Robotics · Computer Science 2023-02-14 Kangcheng Liu

In construction quality monitoring, accurately detecting and segmenting cracks in concrete structures is paramount for safety and maintenance. Current convolutional neural networks (CNNs) have demonstrated strong performance in crack…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Kaiwei Yu , I-Ming Chen , Jing Wu

In this paper, we report the world's first infrastructure-guided communication-enhanced road crack detection pipeline that is effective and implementable on passenger vehicles. We first design a customized communication protocol to transmit…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Haosong Xiao , Yamini Ramesh , Rishabh Shukla , Swarat Sarkar , Chaozhe R. He

Crude oil is an integral component of the world economy and transportation sectors. With the growing demand for crude oil due to its widespread applications, accidental oil spills are unfortunate yet unavoidable. Even though oil spills are…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Abhishek Ramanathapura Satyanarayana , Maruf A. Dhali

Automated pavement crack image segmentation is challenging because of inherent irregular patterns, lighting conditions, and noise in images. Conventional approaches require a substantial amount of feature engineering to differentiate crack…

Computer Vision and Pattern Recognition · Computer Science 2020-07-01 Stephen L. H. Lau , Edwin K. P. Chong , Xu Yang , Xin Wang