Skip to main content
Springer Nature Link
Log in

Object Localization Using Active Partitions and Structural Description

  • Conference paper
Artificial Intelligence and Soft Computing (ICAISC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9119))

Included in the following conference series:

  • 2030 Accesses

Abstract

In this work a method of object localization on the basis of its expected structure is presented. An active partition approach is used for that purpose where, instead of pixels, line segments are used to represent image content. The expectation about object being sought is expressed in the form of model where the expected line segments are specified explicitly. Both image representation and model take into account relations between segments and thus both can be considered as graphs constituting their structural description. The best subsets of line segments are sought in a systematic search process with properly defined model fit function. It allows to identify a subset of segments that resembles the given model even if the segments are detected imprecisely.

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

Access this chapter

Log in via an institution

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

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

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. Tomczyk, A.: Detection of Line Segments. Journal of Applied Computer Science 22(2), 81–90 (2014)

    Google Scholar 

  2. von Gioi, R.G., Jakubowicz, J., Morel, J.-M., Randall, G.: LSD: a Line Segment Detector. Image Processing On Line 2, 35–55 (2012)

    Article  Google Scholar 

  3. Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision, 321–331 (1988)

    Google Scholar 

  4. Caselles, V.: Geometric models for active contours. In: Proceedings of the International Conference on Image Processing, pp. 9–12 (1995)

    Google Scholar 

  5. Cootes, T., Taylor, C., Cooper, D., Graham, J.: Active shape model - their training and application. CVGIP Image Understanding 61(1), 38–59 (1994)

    Article  MATH  Google Scholar 

  6. Tomczyk, A., Szczepaniak, P.S.: Adaptive potential active contours. Pattern Analysis and Application 14, 425–440 (2011)

    Article  MathSciNet  Google Scholar 

  7. Tomczyk, A., Szczepaniak, P.S., Pryczek, M.: Cognitive hierarchical active partitions in distributed analysis of medical images. Journal of Ambient Intelligence and Humanized Computing 4(3), 357–367 (2012)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Information Technology, Lodz University of Technology, ul. Wolczanska 215, 90-924, Lodz, Poland

    Mateusz Jadczyk & Arkadiusz Tomczyk

Authors
  1. Mateusz Jadczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arkadiusz Tomczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafal Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Jadczyk, M., Tomczyk, A. (2015). Object Localization Using Active Partitions and Structural Description. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_65

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19324-3_65

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19323-6

  • Online ISBN: 978-3-319-19324-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics