Skip to main content

Advertisement

Log in

Methods and algorithms of automated two-stage visual recognition of metal-rolling billets

  • Automation in Industry
  • Published:
Automation and Remote Control Aims and scope Submit manuscript

Abstract

The paper presents the methods and algorithms of automatic marking detection employed in the development of automatic marking identification system (AMIS) for billets movement tracking between warehouse and production facilities of JSC Vyksa Steel Works. The system enables automatic monitoring of metal-rolling products; its featured property is the capability of remote recognition over a 3–16 m distance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Forsyth, D. and Ponce, J., Computer Vision: A Modern Approach, Englewood Cliffs: Prentice Hall, 2003.

    Google Scholar 

  2. Chen, I.-H. and Wang, S.J., Efficient Vision-Based Calibration for Visual Surveillance Systems with Multiple PTZ Cameras, IEEE Int. Conf. on Computer Vision Systems, New York, 2006.

    Google Scholar 

  3. Starodubov, D.N. and Stulov, N.N., Program Complex for Processing and Analyzing Object Images in Technical Vision Systems, Programmn. Produkt. Sist., 2006, No. 3, pp. 17–20

    Google Scholar 

  4. Shapiro, L.G. and Stockman, G.C., Computer Vision, Upper Saddle River: Prentice Hall, 2001. Translated under the title Komp’yuteroe zrenie, Moscow: BINOM, 2006.

    Google Scholar 

  5. Klevalin, V.A. and Polivanov, A.Yu., Digital Methods for Identifying Industrial Robots in Technical Vision Systems, Mekhatron., Avtomatiz., Upravl., 2008, No. 5.

  6. Aluze, D., Merienne, F., Dumont, C., and Gorria, P., Vision System for Defect Imaging, Detection and Characterization on a Specular Surface of a 3D Object, Image Vision Comput., 2008, No. 20, pp. 569–580

    Article  Google Scholar 

  7. Rosati, G., Boschetti, G., Biondi, A., and Rossi, A., Real-Time Defect Detection on Highly Reflective Curved Surfaces, Optics Lasers Eng., 2009, Vol. 47, pp. 379–384

    Article  Google Scholar 

  8. Provotorov, A.V. and Orlov, A.A., Developing Methods and System of Industrial Products Automatic Identification Based on Image Analysis on Operated Video Transmitters, in Polzunovsk. Vestn., Barnaul: RITs Altai Gos. Tekh. Univ., 2012, pp. 67–69

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. V. Astaf’ev.

Additional information

Original Russian Text © A.A. Orlov, A.V. Provotorov, A.V. Astaf’ev, 2013, published in Avtomatizatsiya v Promyshlennosti, 2013, No. 10, pp. 53–57.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Orlov, A.A., Provotorov, A.V. & Astaf’ev, A.V. Methods and algorithms of automated two-stage visual recognition of metal-rolling billets. Autom Remote Control 77, 1099–1105 (2016). https://doi.org/10.1134/S000511791606014X

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S000511791606014X

Navigation