A Comparative Review of Image Processing Based Crack Detection Techniques on Civil Engineering Structures

Crack detection and repair of the cracks in engineering structures is essential to ensure serviceability and durability. Traditionally, cracks are detected by the examiner's visual inspection; as a result, crack detection and estimation of characteristics are greatly dependent on the examiner's personal judgment, which has aided in the repair of various structures and evaluation of the crack phenomenon in previous decades. Due to industrial advancement, the number of engineering structures has increased, but compared to that, expertise in the crack detection field did not raise that level. So, a less time-consuming and more accurate approach is needed. The image processing technique works simultaneously to detect the cracks with their attributes. In this context, the development of the algorithm and the implementation procedure is also simple. But some defects such as identifying noises as cracks and weakness in identifying micro-cracks have become significant challenges for this technique. Unable to locate transverse cracks in concrete structures is also a vital issue. So, to develop an accurate method, an extensive survey on the current articles is needed. In this paper, a critical analysis has been done on crack detection through the image processing phenomenon and a detailed literature review to understand the prospects of this method. From the literature review, it was observed that a general structure of CNN-based algorithm with camera images for crack detection could be an efficient approach with higher accuracy.