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The traceability of granite blocks consists in identifying each block with a finite number of color bands which represent a numerical code. This code has to be read several times throughout the manufacturing process, but its accuracy is…

Computer Vision and Pattern Recognition · Computer Science 2022-07-05 Xurxo Rigueira , Javier Martinez , Maria Araujo , Antonio Recaman

The detection of masonry damage is essential for preventing potentially disastrous outcomes. Manual inspection can, however, take a long time and be hazardous to human inspectors. Automation of the inspection process using novel computer…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Elmira Faraji Zonouz , Xiao Pan , Yu-Cheng Hsu , Tony Yang

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

Compared to NDT and health monitoring method for cracks in engineering structures, surface crack detection or identification based on visible light images is non-contact, with the advantages of fast speed, low cost and high precision.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-17 Kailiang Lu

This paper addresses the critical need for automated crack detection in the preservation of cultural heritage through semantic segmentation. We present a comparative study of U-Net architectures, using various convolutional neural network…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Andrea Ranieri , Giorgio Palmieri , Silvia Biasotti

Cracks in concrete structures are very common and are an integral part of this heterogeneous material. Characteristics of cracks induced by standardized tests yield valuable information about the tested concrete formulation and its…

Machine Learning · Computer Science 2025-01-31 Anna Nowacka , Katja Schladitz , Szymon Grzesiak , Matthias Pahn

Numerous image processing techniques (IPTs) have been employed to detect crack defects, offering an alternative to human-conducted onsite inspections. These IPTs manipulate images to extract defect features, particularly cracks in surfaces…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Mohsen Asghari Ilani , Leila Amini , Hossein Karimi , Maryam Shavali Kuhshuri

Automated pavement crack detection and measurement are important road issues. Agencies have to guarantee the improvement of road safety. Conventional crack detection and measurement algorithms can be extremely time-consuming and low…

Computer Vision and Pattern Recognition · Computer Science 2020-02-11 Zhun Fan , Chong Li , Ying Chen , Paola Di Mascio , Xiaopeng Chen , Guijie Zhu , Giuseppe Loprencipe

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

Over the past decade, automated methods have been developed to detect cracks more efficiently, accurately, and objectively, with the ultimate goal of replacing conventional manual visual inspection techniques. Among these methods, semantic…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Nachuan Ma , Rui Fan , Lihua Xie

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

A physics-informed machine learning framework based on holomorphic neural networks is introduced for detecting cracks in two-dimensional solids from strain or displacement data. Crack detection is formulated as an inverse problem in which…

Computational Engineering, Finance, and Science · Computer Science 2026-03-16 Jonas Hund , Nicolas Cuenca , Tito Andriollo

Timely, accurate and automatic detection of pavement cracks is necessary for making cost-effective decisions concerning road maintenance. Conventional crack detection algorithms focus on the design of single or multiple crack features and…

Computer Vision and Pattern Recognition · Computer Science 2019-07-05 Wenjun Liu , Yuchun Huang , Ying Li , Qi Chen

Automatic crack detection is a critical task that has the potential to drastically reduce labor-intensive building and road inspections currently being done manually. Recent studies in this field have significantly improved the detection…

Computer Vision and Pattern Recognition · Computer Science 2020-11-05 Yuki Inoue , Hiroto Nagayoshi

Fracture is one of the main failure modes of engineering structures such as buildings and roads. Effective detection of surface cracks is significant for damage evaluation and structure maintenance. In recent years, the emergence and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-26 Yu Zhang , Lin 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

Current methods of practice for inspection of civil infrastructure typically involve visual assessments conducted manually by trained inspectors. For post-earthquake structural inspections, the number of structures to be inspected often far…

Computer Vision and Pattern Recognition · Computer Science 2018-05-04 Vedhus Hoskere , Yasutaka Narazaki , Tu Hoang , BillieF Spencer

Visual defect assessment is a form of anomaly detection. This is very relevant in finding faults such as cracks and markings in various surface inspection tasks like pavement and automotive parts. The task involves detection of…

Computer Vision and Pattern Recognition · Computer Science 2019-05-31 Manpreet Singh Minhas , John Zelek

The preservation of our cultural heritage is of paramount importance. Thanks to recent developments in digital acquisition techniques, powerful image analysis algorithms are developed which can be useful non-invasive tools to assist in the…

Computer Vision and Pattern Recognition · Computer Science 2013-04-24 Bruno Cornelis , Yun Yang , Joshua T. Vogelstein , Ann Dooms , Ingrid Daubechies , David Dunson

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