Depth-based feature extraction-guided automatic identification tracking of steel products for smart manufacturing in steel 4.0

Chao Yung Hsu, Li Wei Kang, Hsin Yi Lin, Ru Hong Fu, Chih Yang Lin, Ming Fang Weng, Duan Yu Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

To achieve smart manufacturing in Industry 4.0 for steel industry, a smart steel manufacturing framework is considered in this paper, where an automatic identification tracking method for steel products is developed. Existing approaches usually rely on marking or embedding a series of identification codes on the steel surfaces. However, steel-making is usually processed under a very high temperature environment, making it difficult to well embed the identification codes with acceptable quality for further online processing. Therefore, this paper presents a vision-based automatic identification tracking method without needing to embed any identification codes onto the steel product surfaces. The key is to use the essential identity of a steel product without extrinsic information embedded, achieved by extracting visual features from the steel image. Our preliminary results have verified the efficiency of the proposed method.

Original languageEnglish
Title of host publicationProceedings of 4th IEEE International Conference on Applied System Innovation 2018, ICASI 2018
EditorsArtde Donald Kin-Tak Lam, Stephen D. Prior, Teen-Hang Meen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages145-146
Number of pages2
ISBN (Electronic)9781538643426
DOIs
Publication statusPublished - 2018 Jun 22
Externally publishedYes
Event4th IEEE International Conference on Applied System Innovation, ICASI 2018 - Chiba, Japan
Duration: 2018 Apr 132018 Apr 17

Publication series

NameProceedings of 4th IEEE International Conference on Applied System Innovation 2018, ICASI 2018

Conference

Conference4th IEEE International Conference on Applied System Innovation, ICASI 2018
Country/TerritoryJapan
CityChiba
Period2018/04/132018/04/17

Keywords

  • depth image
  • identification tracking
  • Industry 4.0
  • smart manufacturing
  • steel 4.0
  • steel industry

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Modelling and Simulation
  • Biomedical Engineering

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