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Sammanfattning

The Image Foresting Transform (IFT) is a framework for image partitioning, commonly used for interactive segmentation. Given an image where a subset of the image elements (seed-points) have been assigned user-defined labels, the IFT completes the labeling by computing minimal cost paths from all image elements to the seed-points. Each image element is then given the same label as the closest seed-point. In its original form, the IFT produces crisp segmentations, i.e., each image element is assigned the label of exactly one seem-point. Here, we propose a modified version of the JET that computes region boundaries with sub-pixel precision by allowing mixed labels at region boundaries. We demonstrate that the proposed sub-pixel IFT allows properties of the segmented object to be measured with higher precision.

Nyckelord

Image foresting transform; Interactive image segmentation; Sub-pixel precision

Publicerad i

Lecture Notes in Computer Science
2009, volym: 5852, sidor: 201-211
Titel: Combinatorial Image Analysis
Utgivare: Springer-Verlag

Konferens

13th International Workshop on Combinatorial Image Analysis, NOV 24-27, 2009, Playa del Carmen, MEXICO

SLU författare

  • Malmberg, Filip

    • Centre for Image Analysis, Sveriges lantbruksuniversitet

  • Lindblad, Joakim

    • Centre for Image Analysis, Sveriges lantbruksuniversitet

  • Nyström, Ingela

    • Centre for Image Analysis, Sveriges lantbruksuniversitet

UKÄ forskningsämne

Datavetenskap (datalogi)

Publikationens identifierare

  • DOI: https://doi.org/10.1007/978-3-642-10210-3_16
  • ISBN: 978-3-642-10208-0

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/27321