[1] Zhang L, Yang F, Daniel Zhang Y et al. Road crack detection using deep convolutional neural network. [C]∥2016 IEEE International Conference on Image Processing (ICIP), September 25-28, 2016. Phoenix, AZ, USA. New York: IEEE, 3708-3712(2016).

[2] Li L F, Sun R Y. Bridge crack detection algorithm based on image processing under complex background[J]. Laser & Optoelectronics Progress, 56, 061002(2019).

[3] Wang B, Wang X, Chen F et al. Pavement crack recognition based on aerial image[J]. Acta Optica Sinica, 37, 0810004(2017).

[4] Hoang N D, Nguyen Q L. A novel method for asphalt pavement crack classification based on image processing and machine learning[J]. Engineering with Computers, 35, 487-498(2019).

[5] Liu L F, Wu Q S, Yao B B[J]. Bridge crack detection based on Gaussian scale space and SVM Industrial Instrumentation & Automation, 2019, 13-16, 114.

[6] Salman M, Mathavan S, Kamal K et al. Pavement crack detection using the Gabor filter. [C]∥16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), October 6-9, 2013. The Hague, Netherlands. New York: IEEE, 2039-2044(2013).

[7] Zou Q, Cao Y, Li Q Q et al. CrackTree: Automatic crack detection from pavement images[J]. Pattern Recognition Letters, 33, 227-238(2012).

[8] Oliveira H, Correia P L. Automatic road crack detection and characterization[J]. IEEE Transactions on Intelligent Transportation Systems, 14, 155-168(2013).

[9] Wang B X, Wang Z, Zhang Y F et al. Concrete crack region detection based on high-dimensional image feature compressed sensing[J]. Transactions of Beijing Institute of Technology, 39, 343-351(2019).

[10] Zhang S. The study on tunnel crack detection method using image processing technology[D]. Zhenjiang: Jiangsu University of Science and Technology(2017).

[11] Lü Y, Qu S R. A pavement crack image dodging algorithm based on beamlet transform[J]. Journal of Transportation Systems Engineering and Information Technology, 11, 123-128(2011).

[12] Li H T, Chen X D, Xu H Y et al. Bridge crack detection algorithm based on Bilateral-Frangi filter[J]. Laser & Optoelectronics Progress, 56, 181401(2019).

[13] Cha Y J, Choi W, Büyüköztürk O. Deep learning-based crack damage detection using convolutional neural networks[J]. Computer-Aided Civil and Infrastructure Engineering, 32, 361-378(2017).

[14] Chen F C, Jahanshahi M R. NB-CNN: deep learning-based crack detection using convolutional neural network and naïve Bayes data fusion[J]. IEEE Transactions on Industrial Electronics, 65, 4392-4400(2018).

[15] Zhao W, Hua C R, Wang D Y et al. Fault diagnosis of shaft misalignment and crack in rotor system based on MI-CNN[M]. ∥Lecture Notes in Mechanical Engineering. Singapore: Springer Singapore, 529-540(2019).

[16] Cireşan D C, Giusti A, Gambardella L M et al. Mitosis detection in breast cancer histology images with deep neural networks[M]. ∥Medical Image Computing and Computer-Assisted Intervention-MICCAI 2013. Berlin, Heidelberg: Springer Berlin Heidelberg, 411-418(2013).

[17] Yang F, Zhang L, Yu S J et al. Feature pyramid and hierarchical boosting network for pavement crack detection[J]. IEEE Transactions on Intelligent Transportation Systems, 21, 1525-1535(2020).

[18] Shi Y, Cui L M, Qi Z Q et al. Automatic road crack detection using random structured forests[J]. IEEE Transactions on Intelligent Transportation Systems, 17, 3434-3445(2016).

[19] Sun K, Li M J, Liu D et al. -07-20)[2019-10-30]. https: ∥arxiv., org/abs/1806, 00178(2018).

[20] Yi S B, Ju J, Yoon M et al. -05-31)[2019-10-30]. https: ∥arxiv., org/abs/1703, 09938(2018).

[21] Wu T S, Zhang Z J, Liu Y P et al. A lightweight small object detection algorithm based on improved SSD[J]. Infrared and Laser Engineering, 47, 0703005(2018).

[22] Wang J F, Huang Z C. Talab A M A. New binarization method called BM aim to optimize detail of image[J]. Journal of Wuhan University of Technology, 36, 127-132(2014).

[23] Fang Z, Peng H T. Crack width detection on the concrete surface of bridge based on image analysis technology[J]. Journal of Hunan University(Natural Sciences), 39, 7-12(2012).

[24] Jing K. Development of detect cracks in concrete structures based on smart phone[D]. Hangzhou: Zhejiang University of Technology(2016).