This is a large Facility Surface Crack Detection Dataset (FSCDD). FSCDD is composed of our laboratory dataset and those available on the Internet datasets.
The data set is primarily used to study for Facility Surface Cracks Detection, and is not allowed for commercial purposes; If you want to use this data set, you would to refer to the corresponding paper.The link is: https://pan.baidu.com/s/1bUqPjpi_YHEVsSq-dhDHKQ code: 08ia
Tunnel Crack：
@ARTICLE{8777129, author={Qu, Zhong and Chen, Si-Qi and Liu, Yu-Qin and Liu, Ling}, journal={IEEE Transactions on Intelligent Transportation Systems}, title={Linear Seam Elimination of Tunnel Crack Images Based on Statistical Specific Pixels Ratio and Adaptive Fragmented Segmentation}, year={2020}, volume={21}, number={9}, pages={3599-3607}, doi={10.1109/TITS.2019.2929483}}
CRACK500:
@inproceedings{zhang2016road, title={Road crack detection using deep convolutional neural network}, author={Zhang, Lei and Yang, Fan and Zhang, Yimin Daniel and Zhu, Ying Julie}, booktitle={Image Processing (ICIP), 2016 IEEE International Conference on}, pages={3708--3712}, year={2016}, organization={IEEE} }' .
@article{yang2019feature, title={Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection}, author={Yang, Fan and Zhang, Lei and Yu, Sijia and Prokhorov, Danil and Mei, Xue and Ling, Haibin}, journal={arXiv preprint arXiv:1901.06340}, year={2019} }
GAPs384:
@inproceedings{eisenbach2017how, title={How to Get Pavement Distress Detection Ready for Deep Learning? A Systematic Approach.}, author={Eisenbach, Markus and Stricker, Ronny and Seichter, Daniel and Amende, Karl and Debes, Klaus and Sesselmann, Maximilian and Ebersbach, Dirk and Stoeckert, Ulrike and Gross, Horst-Michael}, booktitle={International Joint Conference on Neural Networks (IJCNN)}, pages={2039--2047}, year={2017} }
CFD:
@article{shi2016automatic, title={Automatic road crack detection using random structured forests}, author={Shi, Yong and Cui, Limeng and Qi, Zhiquan and Meng, Fan and Chen, Zhensong}, journal={IEEE Transactions on Intelligent Transportation Systems}, volume={17}, number={12}, pages={3434--3445}, year={2016}, publisher={IEEE} }
AEL:
@article{amhaz2016automatic, title={Automatic Crack Detection on Two-Dimensional Pavement Images: An Algorithm Based on Minimal Path Selection.}, author={Amhaz, Rabih and Chambon, Sylvie and Idier, J{'e}r{^o}me and Baltazart, Vincent} }
cracktree200:
@article{zou2012cracktree, title={CrackTree: Automatic crack detection from pavement images}, author={Zou, Qin and Cao, Yu and Li, Qingquan and Mao, Qingzhou and Wang, Song}, journal={Pattern Recognition Letters}, volume={33}, number={3}, pages={227--238}, year={2012}, publisher={Elsevier} }
李良福,马卫飞,李丽,陆铖.基于深度学习的桥梁裂缝检测算法研究[J].自动化学报,2019,45(09):1727-1742.