International Journal of Scientific Research and Engineering Development

Structural cracks are among the earliest indicators of deterioration in concrete buildings, bridges, and other civil engineering infrastructure. Early identification and assessment of these cracks are essential for ensuring structural safety, serviceability, and timely maintenance. Conventional inspection methods primarily rely on visual observation and manual measurements, which can be time-consuming, labor-intensive, and dependent on the experience of the inspector. Recent advancements in computer vision and image processing have created opportunities for developing automated crack inspection systems capable of supporting engineers during structural assessments.
This review presents an overview of computer vision-based approaches used for crack detection, dimensional estimation, severity assessment, and maintenance planning. The paper discusses the limitations of traditional inspection practices and highlights the potential benefits of integrating image processing techniques into structural inspection workflows. In addition, a conceptual framework for a Smart Crack Identifier and Structural Diagnostic System is introduced, demonstrating how automated image analysis can support preliminary engineering decisionmaking. The study concludes by discussing future research directions, including artificial intelligence, droneassisted inspection, and the integration of structural health monitoring.

Subbulakshmi S, Dr.E.Mohamed Najeeb,"Smart Crack Identifier and Structural Diagnostic System: A Review of Computer Vision-Based Techniques for Structural Crack Inspection" International Journal of Scientific Research and Engineering Development, V9(3): Page(2307-2311) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.