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A New Level-Set Based Algorithm for Bimodal Depth Segmentation

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 7517)

Abstract

In this paper, a new algorithm for bimodal depth segmentation is presented. The method separates the background and the planar objects of arbitrary shapes lying in a certain height above the background using the information from the stereo image pair (more exactly, the background and the objects may lie on two distinct general planes). The problem is solved as a problem of minimising a functional. A new functional is proposed for this purpose that is based on evaluating the mismatches between the images, which contrasts with the usual approaches that evaluate the matches. We explain the motivation for such an approach. The minimisation is carried out by making use of the Euler-Lagrange equation and the level-set function. The experiments show the promising results on noisy synthetic images as well as on real-life images. An example of the practical application of the method is also presented.

Keywords

  • image segmentation
  • stereo correspondence
  • level set

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© 2012 Springer-Verlag Berlin Heidelberg

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Krumnikl, M., Sojka, E., Gaura, J. (2012). A New Level-Set Based Algorithm for Bimodal Depth Segmentation. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P., Zemčík, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2012. Lecture Notes in Computer Science, vol 7517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33140-4_20

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  • DOI: https://doi.org/10.1007/978-3-642-33140-4_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33139-8

  • Online ISBN: 978-3-642-33140-4

  • eBook Packages: Computer ScienceComputer Science (R0)