[go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

A Top-Down Approach for Automatic Dropper Extraction in Catenary Scenes

  • Conference paper
Pattern Recognition and Image Analysis (IbPRIA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5524))

Included in the following conference series:

Abstract

This paper presents an original system for the automatic detection of droppers in catenary staves. Based on a top-down approach, our system exploits a priori knowledge that are used to perform a reliable extraction of droppers. Experiments conducted on a significant database of real catenary stave images show some promising results on this very challenging machine vision application.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Battle, J., Casals, A., Freixenet, J., Martí, J.: A review on strategies for recognizing natural in colour images of outdoor scenes. Image and Vision Computing 18, 515–530 (2000)

    Article  Google Scholar 

  2. Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (1995)

    MATH  Google Scholar 

  3. Kouadio, R., Delcourt, V., Heutte, L., Petitjean, C.: Video based catenary for preventive maintenance on Iris 320. In: Proc. WCRR 2008, Seoul, Korea (2008)

    Google Scholar 

  4. Montreuil, F., Kouadio, R., Petitjean, C., Heutte, L., Delcourt, V.: Automatic extraction of information for catenary scene analysis. In: Proc. EUSIPCO 2008, Lausanne, Switzerland (2008)

    Google Scholar 

  5. Lacoste, C., Descombes, X., Zerubia, J., Baghdadi, N.: Unsupervised line network extraction from remotely sensed images by polyline process. In: Proc. EUSIPCO 2004, Vienna, Austria (2004)

    Google Scholar 

  6. Richter, U., Schneider, R.: Automatische optische Inspektion von Oberleitungen. Elektrische Bahnen 99, 94–100 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. LITIS, Université de Rouen, EA 4108 BP 12, 76801, Saint-Etienne-du-Rouvray, France

    Caroline Petitjean, Laurent Heutte & Régis Kouadio

  2. Direction de l’Innovation et de la Recherche SNCF, 45 rue de Londres, 75379, Paris Cedex 8, France

    Régis Kouadio & Vincent Delcourt

Authors
  1. Caroline Petitjean
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Laurent Heutte
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Régis Kouadio
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vincent Delcourt
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Systems and Robotics, Dept. of Electrical and Computer Eng.-Polo II, University of Coimbra, 3030-290, Coimbra, Portugal

    Helder Araujo

  2. Institute of Biomedical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Ana Maria Mendonça

  3. Dept. de Electrónica e Telecomunicações / IEETA, Universidade de Aveiro, Signal Processing Lab, DETI/IEETA, University of Aveiro, 3810–193, Aveiro, Portugal

    Armando J. Pinho

  4. Departamento de Electricidad y Electrónica, Fac. Ciencia y Tecnología - UPV/EHU, Universidad del País Vasco, Apartado 644, 48080, Bilbao, Spain

    María Inés Torres

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Petitjean, C., Heutte, L., Kouadio, R., Delcourt, V. (2009). A Top-Down Approach for Automatic Dropper Extraction in Catenary Scenes. In: Araujo, H., Mendonça, A.M., Pinho, A.J., Torres, M.I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2009. Lecture Notes in Computer Science, vol 5524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02172-5_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02172-5_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02171-8

  • Online ISBN: 978-3-642-02172-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics