Automated detection of cracks in roads using ground penetrating radar

Abstract

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Quality evaluation of ground improvement by deep cement mixing piles via ground-penetrating radar

“…This creates conditions for using GPR technology to detect the changes in the stratum caused pile construction and the differences in the changes in the strata media between different underground locations. Difference in the electromagnetic properties of underground media can cause changes in the GPR response, specifically manifested in changes in the waveform, amplitude, frequency, phase and related attributes of the GPR signals 40 , 42 , 49 , 50 , 54 , 55 . However, the propagation and response of electromagnetic wave fields under the condition of pile groups are very complex, and it is not easy to fully reveal the propagation laws of electromagnetic waves under such condition.…”

A Review on Driving Control Issues for Smart Electric Vehicles

“…Content may change prior to final publication. Using ground penetrating radar (GPR), an automated road surface crack detection method was built in [159]. GPR detects cracks on the road by electromagnetic reflection.…”

A Hybrid Image Enhancement Algorithm for Effective Concrete Surface Crack Classification

“…The Savitzky-Golay filter increases the signal-to-noise ratio without distorting the image, while the Wiener filter method has fewer computations and better noise resistance. A review of image enhancement algorithms used in the literature on cracked concrete images in different surfaces show a preference for the Canny edge [2], Laplace operator and histogram equalization [9], threshold approach [10], Wavelet transform [2], [11], and Singular Value Decomposition (SVD) [12]. [2] applied the Canny edge detection algorithm to extract structural information from images and dramatically reduce the quantum of data to be processed.…”

“…[11] applied the statistical characteristics of the wavelet coefficient in different frequency bands to maximize the resolution of road surface images. [12] applied the SVD on low contrast asphalt surface images to enhance them prior to detecting regions with prominent cracks. [13] proposed a hybrid method (a combination of the min-max gray level discrimination, Otsu method and shape analysis algorithm) to identify crack defects with better accuracy by boosting the contrast of building surface images.…”