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August 1, 2025Journal of Physics Conference SeriesOpen Access

Artificial intelligence in structural crack detection using image processing techniques

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Authors

NMN R MititeluMRMarius Ionuț RîpanuVEVasile Ermolai

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Overview

Machine learning enhances crack detection in structural images, indicating various risk levels and cost efficiencies.

Key Points

  • AI improves structural inspection by using image processing techniques, leading to faster crack detection and classification.
  • The analysis of images showed differing risk levels: Image 2 had significant crack thickness, while Image 1 showed a low risk.
  • Employing machine learning with image preprocessing and segmentation aids in effective crack monitoring.
  • While offering efficiency, the use of 2D images limits the measurement of crack depth, indicating a need for advanced imaging methods.

Cite This Study

Mititelu et al. (2025) studied this question.

synapsesocial.com/papers/68af4cd3ad7bf08b1ead5f2ehttps://doi.org/10.1088/1742-6596/3071/1/012013
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Application of image processing and deep learning in crack detection of historical structures: a systematic review2026
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  4. 4Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach2024 · 20 citations
  5. 5Crack Vision-AI: A Deep Transfer Learning Framework For Structural Crack Detection Using2026