Crack Detection of 3D Asphalt Pavement Based on Multi-feature Test

被引：0
|
作者：
Qiu Y. [1 ,2 ]
Wang G. [1 ,2 ]
Yang E. [1 ,2 ]
Yu X. [1 ,2 ]
Wang C. [1 ,2 ,3 ]
机构：
[1] School of Civil Engineering, Southwest Jiaotong University, Chengdu
[2] Highway Engineering Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu
[3] School of Civil and Environmental Engineering, Oklahoma State University, Stillwater, 74078, OK
来源：
| 1600年 / Science Press卷 / 55期
关键词：
3D images; Detection algorithm; Image processing; Multi-feature; Pavement cracking; Road engineering;
D O I：
10.3969/j.issn.0258-2724.20180270
中图分类号：
学科分类号：
摘要：
In order to solve the accuracy problems in the crack detection of 3D asphalt pavement, which are mainly caused by low contrast between cracks and the surrounding area and complex pavement textures, a three-step preprocessing was conducted on original 3D images firstly, including size reducing, intensity correction and Gaussian smoothing. Then, three predominant feature tests of tilt-level, Gaussian-distribution and edge-gradient were applied to the image profiles of four directions successively so as to obtain the crack profiles. Moreover, the crack profiles of four directions were merged and denoised to acquire the intact cracks. Finally, according to the roughness of pavement surface, a related parameter in the Gaussian-distribution test was adjusted to realize the crack detection of high accuracy. The experiment result indicates that the proposed algorithm can reach 89.19% of accuracy, 93.69% of recall and 91.06% of F-measure, which outperforms another two typical 3D recognition algorithms based on the theories of 3D shadowing and crack seeds. © 2020, Editorial Department of Journal of Southwest Jiaotong University. All right reserved.
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页码：518 / 524
页数：6
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