Jun 1, 2018 · The objective of crack detection may be of many types depending on the parameter with which the crack detection is made possible. Some of the objective which makes this analysis possible: length, width, depth, position, surface and direction of propagation of the crack.

Apr 16, 2025 · Deep learning-based image processing methods are commonly used for bridge crack detection. Aiming at the problem of missed detections and false positives caused by light, stains, and dense cracks ...

Apr 10, 2025 · Based on these studies, know that the current crack detection methods based on image processing techniques have the following limitations: Although the classification of crack images and non-crack images, crack localization, and crack segmentation can be achieved with high efficiency and high accuracy using a DNN in existing methods, crack quantization …

Aug 12, 2024 · Learn which NDT methods and tools work best for surface and subsurface-level crack detection in industrial assets.

Abstract: Cracks are typical line structures that are of interest in many computer-vision applications. In practice, many cracks, e.g., pavement cracks, show poor continuity and low contrast, which bring great challenges to image-based crack detection by using low-level features.

Therefore, an efficient and innovative algorithm for crack detection is proposed, which utilizes a transformer and a multilevel cross-scale weighted feature fusion module, as well as a progressive transfer learning (TL) strategy.

Traditional bridge crack detection methods rely on a limited number of professionals to conduct on-site manual inspections [1].These inspection personnel need to travel on vehicles and use auxiliary equipment to approach the surface of the bridge components to visually identify cracks and use cameras to record their shapes [2], [3].They also use tape measures for rough length …

Apr 15, 2025 · Crack identification is an essential yet challenging task in structural health monitoring. This study presents a novel method for automatic crack detection based on optical frequency-domain reflectometry (OFDR) sensors, tackling the challenge of extracting crack-induced information from sensor measurements.

Feb 23, 2024 · Crack detection is a long-standing structural health monitoring (SHM) research topic. Cracks can change material behaviour and weaken structural strength. Even tiny cracks can evolve into...

Apr 16, 2025 · The large-scale coal exploitation causes numerous surface cracks in mining zones. These cracks endanger area safety, damage the ecological environment, and threaten local people’s lives. Traditional ground survey methods for crack detection are inefficient, costly, and limited, failing to meet monitoring demands. To address this, this study uses drone images and …

Aug 20, 2020 · Crack detection by means of thermography is steadily increasing in industrial applications. Thermographic crack testing is usually carried out by employing the pulse thermographic method or the Lock-In thermographic method.

Learn why it’s important to detect cracks in industrial settings and how crack detection using deep learning models like Ultralytics YOLOv8 automates this process. When you look at a crack on a surface, it might seem like a small issue, but it's a good early …

Aug 9, 2024 · Based on the main research methods of the 120 documents, we classify them into three crack detection methods: fusion of traditional methods and deep learning, multimodal data fusion, and semantic image understanding.

Contour Detection for Localization: Apply contour detection on the predicted crack masks to effectively outline and visualize cracks. Real-Time Detection: Implement real-time crack detection using live camera feeds to ensure smooth and accurate detection with low latency.

Many nondestructive examination techniques exist for the detection of discrete cracking, as opposed to general creep damage. These are routinely applied at inspection intervals throughout the life of a component and form an indispensable part of a life assessment program.

Cracks are irregular line structures that are of interest in many computer vision applications. Crack detection (e.g., from pavement images) is a challenging ta.

Apr 15, 2025 · This study suggests an enhanced and optimized detection approach based on TransUNet to address the problems of poor crack recognition accuracy and imprecise edge information extraction in complicated backgrounds. The detection model is built upon TransUNet, with the inclusion of Coordinate Attention (CA) module in the convolutional neural network …

Once you have stored your nodemap files either from dic, simulation or from a different source, you reach the heart of our fracture analysis. You can detect crack paths and crack tips fully automatically using our crack detection module.

Jul 2, 2022 · Researchers have explored automated crack detection in concrete infrastructures, emphasizing crack identification, categorization, crack length, and width measurement.

Mar 11, 2014 · As a consequence, numerous crack detection and characterization techniques have been researched and developed in the past decades in the areas of SHM and non-destructive evaluation (NDE).

Aug 14, 2021 · Crack detection is a very laborious task if performed via manual visual inspection. Many infrastructure elements need to be checked regularly and it is therefore not feasible as it will require significant human resources. This may also result in cases where cracks go undetected.

Through this project, we aim to build a reliable and efficient system for detecting cracks in buildings, enhancing safety, and reducing long-term maintenance costs. We also aim to improve the accuracy of detection by overcoming dataset challenges such as background noise and irregular lighting.

Mar 3, 2021 · There are three levels of crack detection from photos: · The image is divided into patches and each patch is assigned a crack or non-crack label. · A rectangle is drawn around any detected crack. · Each pixel is labelled as crack or non-crack.

Nov 21, 2022 · Computer vision-based crack analysis for civil infrastructure has become popular to automatically process inspection imaging data for crack detection, localisation and quantification.

Cracks are usually curve-like structures that are the fo-cus of many computer-vision applications (e.g., road safety inspection and surface inspection of the industrial facili-ties). The existing pixel-based crack segmentation meth-ods rely on time-consuming and costly pixel-level annota-tions.

Jan 27, 2022 · In this paper, a comprehensive literature review of deep learning-based crack detection studies and the contributions they have made to the field is presented.

Reliable detection, location, and sizing of crack-like features. Even cracking virtually invisible to the human eye can still weaken pipeline integrity to the point of catastrophic failure. Baker Hughes pipeline crack detection methods, such as gith weld inspection, and pipeline inspection tools help operators conduct SSC Test for Pipes to ...