Concrete surface crack detection system through OpenCV library

Identification of structural damages such as cracks at an early stage helps in providing effective retrofitting measures to enhance the structure’s serviceable life. An artificial intelligence tool such as computer vision is used to develop a crack detection algorithm based on a visual studio integr...

Full description

Saved in:
Bibliographic Details
Main Authors: Tumrate, Charanjeet Singh, Mishra, Dhaneshwar
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Artificial intelligence
Computer vision
Damage detection
Effectiveness
Flaw detection
Libraries
Real time
Retrofitting
Structural health monitoring
Surface cracks
Surface defects
Visual programming languages
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Identification of structural damages such as cracks at an early stage helps in providing effective retrofitting measures to enhance the structure’s serviceable life. An artificial intelligence tool such as computer vision is used to develop a crack detection algorithm based on a visual studio integrated with the OpenCV library. This new approach provides a robust structural health monitoring system to accurately identify concrete surface defects such as cracks in real-time. The training data and testing data are generated from the database and the algorithm developed is validated. The experimental validation of the developed CV model shows the high accuracy of the proposed algorithm in identifying cracks on concrete surfaces. The integration of vision technology with health monitoring of concrete by detecting surface cracks exhibit strong potential towards infrastructure health sustainability.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0221510