Review on computer vision-based crack detection and quantification methodologies for civil structures

A critical review and comparative study on image segmentation-based techniques for pavement crack detection

(2022) Narges Kheradmandi et al.   CONSTRUCTION AND BUILDING MATERIALS

Attention recurrent residual U-Net for predicting pixel-level crack widths in concrete surfaces

(2022) Aravinda S Rao et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Multistage semisupervised active learning framework for crack identification, segmentation, and measurement of bridges

(2022) Yue Zheng et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Intelligent crack detection based on attention mechanism in convolution neural network

(2021) Xiaoning Cui et al.   ADVANCES IN STRUCTURAL ENGINEERING

Attention-guided analysis of infrastructure damage with semi-supervised deep learning

(2021) Enes Karaaslan et al.   AUTOMATION IN CONSTRUCTION

Balanced semisupervised generative adversarial network for damage assessment from low‐data imbalanced‐class regime

(2021) Yuqing Gao et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Cost-effective system for detection and quantification of concrete surface cracks by combination of convolutional neural network and image processing techniques

(2021) Pengyong Miao et al.   CONSTRUCTION AND BUILDING MATERIALS

A UAV-based machine vision method for bridge crack recognition and width quantification through hybrid feature learning

(2021) Xiong Peng et al.   CONSTRUCTION AND BUILDING MATERIALS

A review on the attention mechanism of deep learning

(2021) Zhaoyang Niu et al.   NEUROCOMPUTING

Machine vision-based surface crack analysis for transportation infrastructure

(2021) Wenbo Hu et al.   AUTOMATION IN CONSTRUCTION

Computer Vision–Based Human Comfort Assessment of Stadiums

(2020) Ozan Celik et al.   JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES

Generative adversarial network for road damage detection

(2020) Hiroya Maeda et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Concrete crack detection and quantification using deep learning and structured light

(2020) Song Ee Park et al.   CONSTRUCTION AND BUILDING MATERIALS

A review of computer vision–based structural health monitoring at local and global levels

(2020) Chuan-Zhi Dong et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Imaging-based crack detection on concrete surfaces using You Only Look Once network

(2020) Jianghua Deng et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Automated pavement crack detection and segmentation based on two‐step convolutional neural network

(2020) Jingwei Liu et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

A cost effective solution for pavement crack inspection using cameras and deep neural networks

(2020) Qipei Mei et al.   CONSTRUCTION AND BUILDING MATERIALS

A real-time detection approach for bridge cracks based on YOLOv4-FPM

(2020) Zhenwei Yu et al.   AUTOMATION IN CONSTRUCTION

Rapid Surface Damage Detection Equipment for Subway Tunnels Based on Machine Vision System

(2020) Zhen Huang et al.   Journal of Infrastructure Systems

Automatic pixel-level multiple damage detection of concrete structure using fully convolutional network

(2019) Shengyuan Li et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

(2019) Billie F. Spencer et al.   Engineering

A fast adaptive crack detection algorithm based on a double-edge extraction operator of FSM

(2019) Qijun Luo et al.   CONSTRUCTION AND BUILDING MATERIALS

Artificial Intelligence Assisted Infrastructure Assessment using Mixed Reality Systems

(2019) Enes Karaaslan et al.   TRANSPORTATION RESEARCH RECORD

Concrete crack detection with handwriting script interferences using faster region‐based convolutional neural network

(2019) Jianghua Deng et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Image-based concrete crack detection in tunnels using deep fully convolutional networks

(2019) Yupeng Ren et al.   CONSTRUCTION AND BUILDING MATERIALS

Pixel-Level Cracking Detection on 3D Asphalt Pavement Images Through Deep-Learning- Based CrackNet-V

(2019) Yue Fei et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection

(2019) Fan Yang et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Tunnel structural inspection and assessment using an autonomous robotic system

(2018) Elisabeth Menendez et al.   AUTOMATION IN CONSTRUCTION

Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network

(2018) Hoang Nhat-Duc et al.   AUTOMATION IN CONSTRUCTION

Road Damage Detection and Classification Using Deep Neural Networks with Smartphone Images

(2018) Hiroya Maeda et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion

(2018) Fu-Chen Chen et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

(2018) Liang-Chieh Chen et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Crack and Noncrack Classification from Concrete Surface Images Using Machine Learning

(2018) Hyunjun Kim et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Surface fatigue crack identification in steel box girder of bridges by a deep fusion convolutional neural network based on consumer-grade camera images

(2018) Yang Xu et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Deep learning based image recognition for crack and leakage defects of metro shield tunnel

(2018) Hong-wei Huang et al.   TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY

Automatic Pixel-Level Crack Detection and Measurement Using Fully Convolutional Network

(2018) Xincong Yang et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete

(2018) Sattar Dorafshan et al.   CONSTRUCTION AND BUILDING MATERIALS

Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization

(2018) Xiao Liang   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique

(2018) Byunghyun Kim et al.   SENSORS

Autonomous concrete crack detection using deep fully convolutional neural network

(2018) Cao Vu Dung et al.   AUTOMATION IN CONSTRUCTION

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

(2017) Shaoqing Ren et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Recognition of asphalt pavement crack length using deep convolutional neural networks

(2017) Zheng Tong et al.   Road Materials and Pavement Design

Railway bridge structural health monitoring and fault detection: State-of-the-art methods and future challenges

(2017) Matteo Vagnoli et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Image Based Techniques for Crack Detection, Classification and Quantification in Asphalt Pavement: A Review

(2016) H. Zakeri et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

Bridge deck delamination identification from unmanned aerial vehicle infrared imagery

(2016) A. Ellenberg et al.   AUTOMATION IN CONSTRUCTION

Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection

(2016) Rabih Amhaz et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Automatic Road Crack Detection Using Random Structured Forests

(2016) Yong Shi et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Concrete Crack Assessment Using Digital Image Processing and 3D Scene Reconstruction

(2016) Yu-Fei Liu et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Detection crack in image using Otsu method and multiple filtering in image processing techniques

(2016) Ahmed Mahgoub Ahmed Talab et al.   OPTIK

Improved digital photogrammetry technique for crack monitoring

(2015) Satoshi Nishiyama et al.   ADVANCED ENGINEERING INFORMATICS

A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

(2015) Christian Koch et al.   ADVANCED ENGINEERING INFORMATICS

Thin crack observation in a reinforced concrete bridge pier test using image processing and analysis

(2015) Yuan-Sen Yang et al.   ADVANCES IN ENGINEERING SOFTWARE

Vision-Based Automated Crack Detection for Bridge Inspection

(2015) Chul Min Yeum et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

(2015) Kaiming He et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Use of a Self-Organizing Map for Crack Detection in Highly Textured Pavement Images

(2015) S. Mathavan et al.   Journal of Infrastructure Systems

A stereovision-based crack width detection approach for concrete surface assessment

(2015) Baohua Shan et al.   KSCE Journal of Civil Engineering

Deep learning

(2015) Yann LeCun et al.   NATURE

A Vision-Based Sensor for Noncontact Structural Displacement Measurement

(2015) Dongming Feng et al.   SENSORS

Long-distance precision inspection method for bridge cracks with image processing

(2013) Gang Li et al.   AUTOMATION IN CONSTRUCTION

Image-based retrieval of concrete crack properties for bridge inspection

(2013) R.S. Adhikari et al.   AUTOMATION IN CONSTRUCTION

Robust Method for Automated Segmentation of Frames with/without Distress from Road Surface Video Clips

(2013) Huidrom Lokeshwor et al.   JOURNAL OF TRANSPORTATION ENGINEERING

Crack detection of reinforced concrete bridge using video image

(2013) Xue-jun Xu et al.   Journal of Central South University

Adaptive vision-based crack detection using 3D scene reconstruction for condition assessment of structures

(2012) Mohammad R. Jahanshahi et al.   AUTOMATION IN CONSTRUCTION

Visual retrieval of concrete crack properties for automated post-earthquake structural safety evaluation

(2011) Zhenhua Zhu et al.   AUTOMATION IN CONSTRUCTION

A Fully Non-Contact Ultrasonic Propagation Imaging System for Closed Surface Crack Evaluation

(2011) D. Dhital et al.   EXPERIMENTAL MECHANICS

An innovative methodology for detection and quantification of cracks through incorporation of depth perception

(2011) Mohammad R. Jahanshahi et al.   MACHINE VISION AND APPLICATIONS

CrackTree: Automatic crack detection from pavement images

(2011) Qin Zou et al.   PATTERN RECOGNITION LETTERS

A robust automatic crack detection method from noisy concrete surfaces

(2010) Yusuke Fujita et al.   MACHINE VISION AND APPLICATIONS

Practical image measurement of crack width for real concrete structure

(2009) Tomoyuki Yamaguchi et al.   Electronics and Communications in Japan

Fast crack detection method for large-size concrete surface images using percolation-based image processing

(2009) Tomoyuki Yamaguchi et al.   MACHINE VISION AND APPLICATIONS

Integration of computer imaging and sensor data for structural health monitoring of bridges

(2009) R Zaurin et al.   Smart Materials and Structures

A survey and evaluation of promising approaches for automatic image-based defect detection of bridge structures

(2008) Mohammad R. Jahanshahi et al.   Structure and Infrastructure Engineering