Accurate Crack Identification of Concrete Structures Based on Deep Bi-LSTM Model

Cracks in the concrete's exterior are important warning signs of structural degradation and deterioration. The most prevalent method, manual visual examination, is inefficient from several angles including cost, time, accuracy, and safety. Alternative methods exist, such as those based on computer vision, which can automatically extract crack information from photographs. Since both texts and cracks are made up of lines and curves, image binarization, which was developed for text detection, can be successfully applied to fracture identification that can be distinguished from one another. Binarization is method and parameter dependent, making it difficult to standardize crack identification using images. They look into the use of image binarization for spotting cracks, analyzing five popular binarization techniques to see which ones work best and comparing their relative performance. Errors in estimated crack widths are minimized by processing crack images in order to acquire ideal parameters.