Year: 2025
Type: article
Abstract: This paper explores the application of machine learning algorithms combined with image processing techniques for the detection of cracks in concrete structures. Specifically, it focuses on a color-based crack detection approach using image analysis to enhance the accuracy and efficiency of identifying structural defects. By leveraging advanced image processing methods, the system can extract visual features that differentiate between cracked and uncracked surfaces. The study also aims to develop an automated classification model capable of distinguishing between images of cracked and non-cracked concrete, thereby minimizing the need for manual inspection and improving the reliability of structural health monitoring.
Authors: Leul Deribe Abera, Yancheng Li, Shaoqi Li
Institution: Nanjing Tech University
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410930628