Abstract
Numerous studies have employed computer vision algorithms to analyze images of concrete damage. Therefore, conducting an image processing survey to detect concrete damage is very crucial. Thus, an image processing algorithm analysis survey to detect concrete damage was conducted using various algorithms and types of data from the last decade. The data observed were the first is damage to concrete, which included surface cracks, hairlines, crack width, patterns, holes, diagonal cracks, longitudinal cracks, and transverse cracks. The second part is figuring out where roads, bridges, and buildings are. The third is data sources like digital cameras, cameras built into phones, camera sensor systems, and unmanned aerial vehicles (UAVs). The study's findings indicate that image processing algorithms will play an essential role in future assessment research on the automation of concrete damage detection. This is particularly the case in high-risk regions for security reasons, and UAV technology is required to reach these locations.
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