| Issue |
SHS Web Conf.
Volume 140, 2022
2022 International Conference on Information Technology in Education and Management Engineering (ITEME2022)
|
|
|---|---|---|
| Article Number | 01016 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/shsconf/202214001016 | |
| Published online | 25 May 2022 | |
Research on recognizing required items based on opencv and machine learning
1
Department of Electronic Studies, Software Enginerring Institute of Guangzhou, Guangzhou 510980, China
2
Algorithm Engineer, Shenzhen Huoyan intelligent Co. Ltd, Shenzhen 518000, China
* Corresponding author: 723539726@qq.com
Starting from the background of the outbreak of New Coronavirus, in order to realize the function of automatically identifying the required items by machine, the support vector machine algorithm in the neural network and the traditional computer vision algorithm opencv were used. The software developed by pycharm and python programming language was used to compile automatically a software to identify whether the required items were filled out. And on the basis of completing the software, it is connected to the embedded device high-speed clapper. It is applied to Fuzhou Customs to help the customs staff review the health form and declaration card of inbound and outbound passengers, which not only saves the time of staff and passengers, but also contributes to the prevention and control of epidemic situation to a certain extent.
Key words: SVM algorithm / Computer vision / Identification of required items
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.