scholarly journals Pavement crack detection using non‐local theory and iterative sampling

2021 ◽  
Author(s):  
Zixian Wei ◽  
Tao SUN ◽  
Yuhao Wu ◽  
Liqing Zhou ◽  
Xiaoli Ruan

2000 ◽  
Vol 10 (PR9) ◽  
pp. Pr9-485-Pr9-490 ◽  
Author(s):  
T. A. Khantuleva
Keyword(s):  


2020 ◽  
Vol 13 (6) ◽  
pp. 1-9
Author(s):  
CHEN Xiao-Dong ◽  
◽  
AI Da-Hang ◽  
ZHANG Jia-Chen ◽  
CAI Huai-Yu ◽  
...  


2021 ◽  
Author(s):  
Wenning Huang ◽  
Guijie Zhu ◽  
Zhun Fan ◽  
Wenji Li ◽  
Yibiao Rong ◽  
...  


2021 ◽  
Author(s):  
Nima Safaei ◽  
Omar Smadi ◽  
Babak Safaei ◽  
Arezoo Masoud

<p>Cracks considerably reduce the life span of pavement surfaces. Currently, there is a need for the development of robust automated distress evaluation systems that comprise a low-cost crack detection method for performing fast and cost-effective roadway health monitoring practices. Most of the current methods are costly and have labor-intensive learning processes, so they are not suitable for small local-level projects with limited resources or are only usable for specific pavement types.</p> <p>This paper proposes a new method that uses an improved version of the weighted neighborhood pixels segmentation algorithm to detect cracks in 2-D pavement images. This method uses the Gaussian cumulative density function as the adaptive threshold to overcome the drawback of fixed thresholds in noisy environments. The proposed algorithm was tested on 300 images containing a wide range of noise representative of different noise conditions. This method proved to be time and cost-efficient as it took less than 3.15 seconds per 320 × 480 pixels image for a Xeon (R) 3.70 GHz CPU processor to determine the detection results. This makes the model a perfect choice for county-level pavement maintenance projects requiring cost-effective pavement crack detection systems. The validation results were promising for the detection of low to severe-level cracks (Accuracy = 97.3%, Precision = 79.21%, Recall= 89.18% and F<sub>1</sub> score = 83.9%).</p>



2021 ◽  
Vol 2021 (7) ◽  
Author(s):  
Marco Frasca ◽  
Anish Ghoshal

Abstract We investigate the non-perturbative regimes in the class of non-Abelian theories that have been proposed as an ultraviolet completion of 4-D Quantum Field Theory (QFT) generalizing the kinetic energy operators to an infinite series of higher-order derivatives inspired by string field theory. We prove that, at the non-perturbative level, the physical spectrum of the theory is actually corrected by the “infinite number of derivatives” present in the action. We derive a set of Dyson-Schwinger equations in differential form, for correlation functions till two-points, the solution for which are known in the local theory. We obtain that just like in the local theory, the non-local counterpart displays a mass gap, depending also on the mass scale of non-locality, and show that it is damped in the deep UV asymptotically. We point out some possible implications of our result in particle physics and cosmology and discuss aspects of non-local QCD-like scenarios.



2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Hongwei Lei ◽  
Jianlian Cheng ◽  
Qi Xu

This article introduces the application of image recognition technology in cement pavement crack detection and put forward to method for determining threshold about grayscale stretching. the algorithm is designed about binarization which has a self-adaptive characteristic. After the image is preprocessed, we apply 2D Wavelet and Laplace operator to process the image. According to the characteristic of pixel of gray image, an algorithm designed on binarization for Binary image. The feasibility of this method can be verified the image processed by comparing with the results of three algorithms: Otsu method, iteration method and fixed threshold method.





1952 ◽  
Vol 8 (1) ◽  
pp. 133-134
Author(s):  
N. Shono
Keyword(s):  


Sign in / Sign up

Export Citation Format

Share Document