Novel Automatic Pavement Crack Detection Algorithm

Authors

Shangbing Gao, 1. College of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223001, China;;
Xie Zheng, 1. College of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223001, China;;
Zhigeng Pan, 1. College of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223001, China;;2. Virtual Reality and Human-computer Interaction Research Center, Hangzhou Normal University, Hangzhou 311121, China;
Fangzhe Qin, 1. College of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223001, China;;
Li Rui, 1. College of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223001, China;;

Abstract

Abstract: The complexity of noises covers a wide area of actual road images which causes that it is difficult to detect cracks. An automatic pavement crack detection algorithm was proposed in view of the characteristics of crack image in pavement disease. Gray-scale correction and filtering was used to preprocess the crack image. The maximum interclass variance method and Canny operator were used to detect the edge of the disease image, and then the localization and accurate segmentation algorithm was proposed for the crack image based on the maximum connectivity of the crack in the fracture image. The convolution neural network algorithm was used to recognize the pavement cracks. The experimental results show that the proposed method is superior to other advanced algorithms on the crack detection efficiency, and robust to the different types of crack images.

Recommended Citation

Gao, Shangbing; Zheng, Xie; Pan, Zhigeng; Qin, Fangzhe; and Rui, Li (2020) "Novel Automatic Pavement Crack Detection Algorithm," Journal of System Simulation: Vol. 29: Iss. 9, Article 18.
DOI: 10.16182/j.issn1004731x.joss.201709018
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss9/18

First Page

2009

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201709018

Last Page

2015

CLC

TP391.4

Recommended Citation

Gao Shangbing, Xie Zheng, Pan Zhigeng, Qin Fangzhe, Li Rui. Novel Automatic Pavement Crack Detection Algorithm[J]. Journal of System Simulation, 2017, 29(9): 2009-2015.

Corresponding Author

Shangbing Gao,

DOI

10.16182/j.issn1004731x.joss.201709018