@inproceedings{ca96201d96a24eb7bd1e02244ccf7f98,
title = "Surface defect detection of plaster coating based on machine vision",
abstract = "As a kind of traditional Chinese Medicine, plaster has been favored by more and more patients because of its unique advantages in the treatment of diseases. For the coating of plaster, its quality is very important to the plaster. Therefore, coating surface defect detection is very necessary. The current mainstream detection method is manual inspection, there are many disadvantages in this, such as extremely low efficiency and bad for health. In light of this situation, a set of plaster coating quality automatic detection system based on machine vision has been proposed in this paper. Through a detailed analysis of the coating defects, a set of image detection algorithms have been given. It can be found from the experimental results that the algorithm can identify the type of defects and locate the position precisely. The error detection rate is low, and the robustness is good.",
keywords = "Defect Detection, Image Processing, Machine Vision, Plaster Coating",
author = "Huan Wu and Huifu Luo and Wei Zhu and Yanghong Wang and Qiang Zhang and Binwu Ma and Yanzhu Yang and Hui Fan and Hongwei Xu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Unmanned Systems, ICUS 2017 ; Conference date: 27-10-2017 Through 29-10-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICUS.2017.8278354",
language = "English",
series = "Proceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "277--281",
editor = "Xin Xu",
booktitle = "Proceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017",
address = "United States",
}