Treffer: CONCRETE CRACK DETECTION TECHNIQUES USING IMAGE PROCESSING AND MACHINE LEARNING ALGORITHMS

Title:
CONCRETE CRACK DETECTION TECHNIQUES USING IMAGE PROCESSING AND MACHINE LEARNING ALGORITHMS
Publisher Information:
Zenodo
Publication Year:
2025
Collection:
Zenodo
Document Type:
Fachzeitschrift article in journal/newspaper
Language:
unknown
ISSN:
2456-9348
DOI:
10.5281/zenodo.15619572
Rights:
Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number:
edsbas.365110D4
Database:
BASE

Weitere Informationen

This project presents an intelligent system for detecting cracks in concrete structures using image processingtechniques combined with machine learning algorithms such as Support Vector Machine (SVM) andConvolutional Neural Networks (CNN). Developed in Python using the Visual Studio platform, the systempreprocesses input images through steps like gamma correction, grayscale conversion, and noise reduction toenhance crack visibility. It then uses SVM for binary classification of crack regions and a CNN model to improveprecision in localized patch-based crack detection. This approach automates structural inspection with highaccuracy and reliability.