Academic Journal of Computing & Information Science, 2023, 6(1); doi: 10.25236/AJCIS.2023.060113.
Wang Zheng, Guo Jianxin, Hu Chengyu, Qiao Fengkang
School of Electronic Information Engineering, Xijing University, Xi’an, Shaanxi, 710123, China
In order to solve the shortcomings such as low efficiency and great risk of detection and recognition algorithm of road surface, this paper studies the algorithm program of detection and recognition of road surface from the Angle of digital image processing based on computer road and track automation technology, and makes many parameter calculations for horizontal, longitudinal, massive and mesh cracks of road surface. The results show that compared with the traditional detection and recognition methods, the algorithm program studied in this paper effectively improves the measurement accuracy of pavement cracks and the accuracy of crack identification, and the program has high feasibility in road detection and recognition.
Crack in Road Surface; Digital Image Processing; Identification of Cracks
Wang Zheng, Guo Jianxin, Hu Chengyu, Qiao Fengkang. Research on Pavement Crack Detection and Recognition Algorithm. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 1: 83-98. https://doi.org/10.25236/AJCIS.2023.060113.
 Jiayi H. Research on Pavement crack Detection Algorithm based on OpenCV [D]. Harbin: Harbin Engineering University, 2017.
 Weiye W, Xianfu Y. Urban road construction quality standardization management [M]. Hangzhou: Zhejiang Gongshang University Press, 2018.
 Baoan H, Rong C. Research on pavement crack image recognition algorithm [J]. Digital Technology and Applications, 2015(1): 127.
 Shao B. Research on image detection algorithm of asphalt pavement crack [D]. Xian: Chang 'an University, 2008.
 Peng B, Jiang Y S, Pu Y. Pavement Crack Detection Algorithm Based on Bi-Layer Connectivity Checking [J]. Journal of Highway & Transportation Research & Development, 2014, 8(4): 37-46.
 Zedong Q. Research on automatic crack recognition Algorithm of Asphalt pavement based on intelligent image processing [D]. Nanjing: Southeast University, 2014.
 Aijun X. Research on common diseases and maintenance treatment technology of highway asphalt pavement [J]. Heilongjiang Communications Technology, 2012, 35(1): 11-12.
 Yu X. Research on key algorithms in vehicle detection [D]. Shanghai: Shanghai Jiao Tong University, 2009.
 Wanli W. Research on road defect detection and recognition algorithm [D]. Wuhan: Wuhan Institute of Technology, 2015.
 Changrong X. Design and research of pavement crack detection system [D]. Xian: Chang 'an University, 2008.
 Dejin Z, Qingquan L, Ying C, et al. An asphalt pavement crack detection method based on spatial aggregation characteristics [J]. Acta Automatica Sinica, 2016, 42(3): 443-454.
 Hang Z. High-resolution No.1 remote sensing image segmentation method based on full convolutional network [D]. Taian: Shandong Agricultural University, 2018.
 Bin Q, Zhenmin T, Xiaobo S, et al. Pavement crack detection based on multi - feature manifold learning and matrix decomposition [J]. Journal of Scientific Instrument, 2016, 37(7): 1639-1646.
 Yingping W. Research on Improved Face recognition Algorithm based on compressed sensing [D]. Hanzhou: Zhejiang University of Technology, 2017.
 Na L. Urban pavement crack detection based on image processing technology [D]. Fuxin: Liaoning Technical University, 2015.
 Ke Z. Research on Pavement crack image Automatic recognition System [D].Xian: Chang 'an University, 2009.
 Xinghan Q. Research on Pavement Crack detection and recognition based on image segmentation [D]. Chongqing: Chongqing Jiaotong University, 2012.
 Xu H. Research on image - based pavement crack detection technology [D]. Tianjin: Hebei University of Technology, 2016.
 Meilin H, Li W. Design of pavement crack detection and recognition system [J]. Naval Electronic Engineering, 2020, 40(8): 151-154.
 Chong Z. Pavement crack detection and analysis based on MMS image [D]. Beijing: Beijing University of Civil Engineering and Architecture, 2017.
 Bo P, Yangsheng J, Yun P. Automatic pavement crack classification algorithm based on digital image processing [J]. China Journal of Highway and Transport, 2014, 27(9): 10-18.
 Henrique O, Paulo L C. Identifying and retrieving distress images from road Pavement Surveys[J]. IEEE, 2008: 57-60.