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Cracks provide an essential indicator of infrastructure performance degradation, and achieving high-precision pixel-level crack segmentation is an issue of concern. Unlike the common research paradigms that adopt novel artificial…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Zhili He , Wang Chen , Jian Zhang , Yu-Hsing Wang

Surface cracks are a very common indicator of potential structural faults. Their early detection and monitoring is an important factor in structural health monitoring. Left untreated, they can grow in size over time and require expensive…

Computer Vision and Pattern Recognition · Computer Science 2022-02-09 Jacob König , Mark Jenkins , Mike Mannion , Peter Barrie , Gordon Morison

Automating the current bridge visual inspection practices using drones and image processing techniques is a prominent way to make these inspections more effective, robust, and less expensive. In this paper, we investigate the development of…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Andrii Kompanets , Gautam Pai , Remco Duits , Davide Leonetti , Bert Snijder

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

This paper presents a pilot study introducing a multimodal fusion framework for the detection and analysis of bridge defects, integrating Non-Destructive Evaluation (NDE) techniques with advanced image processing to enable precise…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Ravi Datta Rachuri , Duoduo Liao , Samhita Sarikonda , Datha Vaishnavi Kondur

Safety-critical infrastructures, such as bridges, are periodically inspected to check for existing damage, such as fatigue cracks and corrosion, and to guarantee the safe use of the infrastructure. Visual inspection is the most frequent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Andrii Kompanets , Remco Duits , Davide Leonetti , Nicky van den Berg , H. H. , Snijder

Image data has a great potential of helping conventional visual inspections of civil engineering structures due to the ease of data acquisition and the advantages in capturing visual information. A variety of techniques have been proposed…

Computer Vision and Pattern Recognition · Computer Science 2018-05-17 Yasutaka Narazaki , Vedhus Hoskere , Tu A. Hoang , Billie F. Spencer

To improve the efficiency and reduce the labour cost of the renovation process, this study presents a lightweight Convolutional Neural Network (CNN)-based architecture to extract crack-like features, such as cracks and joints. Moreover,…

Image and Video Processing · Electrical Eng. & Systems 2021-05-25 Jiesheng Yang , Fangzheng Lin , Yusheng Xiang , Peter Katranuschkov , Raimar J. Scherer

Image data has a great potential of helping post-earthquake visual inspections of civil engineering structures due to the ease of data acquisition and the advantages in capturing visual information. A variety of techniques have been applied…

Computer Vision and Pattern Recognition · Computer Science 2018-05-17 Yasutaka Narazaki , Vedhus Hoskere , Tu A. Hoang , Billie F. Spencer

Ageing structures require periodic inspections to identify structural defects. Previous work has used geometric distortions to locate cracks in synthetic masonry bridge point clouds but has struggled to detect small cracks. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-09-04 Yixiong Jing , Wei Lin , Brian Sheil , Sinan Acikgoz

Due to cyclic loading and fatigue stress cracks are generated, which affect the safety of any civil infrastructure. Nowadays machine vision is being used to assist us for appropriate maintenance, monitoring and inspection of concrete…

Computer Vision and Pattern Recognition · Computer Science 2020-09-23 Babloo Kumar , Sayantari Ghosh

Crack detection plays a crucial role in civil infrastructures, including inspection of pavements, buildings, etc., and deep learning has significantly advanced this field in recent years. While numerous technical and review papers exist in…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Xinan Zhang , Haolin Wang , Yung-An Hsieh , Zhongyu Yang , Anthony Yezzi , Yi-Chang Tsai

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

Flexible road pavements deteriorate primarily due to traffic and adverse environmental conditions. Cracking is the most common deterioration mechanism; the surveying thereof is typically conducted manually using internationally defined…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Hermann Tapamo , Anna Bosman , James Maina , Emile Horak

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

Adequate bridge inspection is increasingly challenging in many countries due to growing ailing stocks, compounded with a lack of staff and financial resources. Automating the key task of visual bridge inspection, classification of defects…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Johannes Flotzinger , Fabian Deuser , Achref Jaziri , Heiko Neumann , Norbert Oswald , Visvanathan Ramesh , Thomas Braml

Recognising reinforced concrete defects (RCDs) is a crucial element for determining the structural integrity, traffic safety and durability of bridges. However, most of the existing datasets in the RCD domain are derived from a small number…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Johannes Flotzinger , Philipp J. Rösch , Norbert Oswald , Thomas Braml

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

The existence of cracks and other damages pose a significant threat to the safe operation of transportation infrastructure. Traditional manual detection and ultrasound equipment testing consume a lot of time and resources. With the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-17 Yuwei Duan

Cracking is a common failure mode in asphalt concrete (AC) pavements. Many tests have been developed to characterize the fracture behavior of AC. Accurate crack detection during testing is crucial to describe AC fracture behavior. This…

Computer Vision and Pattern Recognition · Computer Science 2023-05-10 Zehui Zhu , Imad L. Al-Qadi
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