Vision-Based Automatic Identification Tracking of Steel Products for Intelligent Steel Manufacturing

Chao Yung Hsu, Li Wei Kang, Teng Yi You, Wei Chen Jhong

研究成果: 書貢獻/報告類型會議論文篇章

6 引文 斯高帕斯(Scopus)

摘要

To achieve intelligent manufacturing in Industry 4.0 for steel industry, this paper considers a smart steel manufacturing framework, where an automatic identification tracking method for steel products is proposed. Automatically online tracking and identifying steel products on a production line is essential for intelligent manufacturing management since those products would be frequently moved and processed at different locations on the product flow. Current approaches usually rely on embedding or marking a series of characters (or identification codes) on the steel surface. However, steel-making process is usually conducted under a high temperature environment, making it difficult to well embed the identification codes with high quality and further automatically well recognize them online. To tackle the problem, this paper presents a novel vision-based automatic identification tracking framework without needing to embed any identification codes into the steel product. The key is to employ the essential identity of a steel product without any extrinsic information embedded, achieved by extracting visual features from the product. The presented preliminary results have verified the efficiency of the proposed method, which will be further improved in the future.

原文英語
主出版物標題Proceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017
發行者Institute of Electrical and Electronics Engineers Inc.
頁面376-377
頁數2
ISBN(電子)9781538629369
DOIs
出版狀態已發佈 - 2017 12月 28
對外發佈
事件19th IEEE International Symposium on Multimedia, ISM 2017 - Taichung, 臺灣
持續時間: 2017 12月 112017 12月 13

出版系列

名字Proceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017
2017-January

其他

其他19th IEEE International Symposium on Multimedia, ISM 2017
國家/地區臺灣
城市Taichung
期間2017/12/112017/12/13

ASJC Scopus subject areas

  • 媒體技術
  • 感覺系統

指紋

深入研究「Vision-Based Automatic Identification Tracking of Steel Products for Intelligent Steel Manufacturing」主題。共同形成了獨特的指紋。

引用此