Color-based Crack Detection using Image Analysis

Leul Deribe Abera*, Yancheng Li, Shaoqi Li

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.

Keywords

deep learning; machine learning; neural networks; crack detection.

Cite This Article

Abera, L. D., Li, Y., Li, S. (2025). Color-based Crack Detection using Image Analysis. International Journal of Scientific Advances (IJSCIA), Volume 6| Issue 3: May-Jun 2025, Pages 482-485 URL: https://www.ijscia.com/wp-content/uploads/2025/05/Volume6-Issue3-May-Jun-No.881-482-485.pdf

Volume 6 | Issue 3: May – Jun 2025