Automatic image segmentation using a deformable model based on charged particles

A.C. Jalba, M.H.F. Wilkinson, J.B.T.M. Roerdink

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    9 Citations (Scopus)
    2 Downloads (Pure)

    Abstract

    We present a method for automatic segmentation of grey-scale images, based on a recently introduced deformable model, the charged-particle model (CPM). The model is inspired by classical electrodynamics and is based on a simulation of charged particles moving in an electrostatic field. The charges are attracted towards the contours of the objects of interest by an electrostatic field, whose sources are computed based on the gradient-magnitude image. Unlike the case of active contours, extensive user interaction in the initialization phase is not mandatory, and segmentation can be performed automatically. To demonstrate the reliability of the model, we conducted experiments on a large database of microscopic images of diatom shells. Since the shells are highly textured, a post-processing step is necessary in order to extract only their outlines.
    Original languageEnglish
    Title of host publicationImage Analysis and Recognition (Proceedings International Conference, ICIAR 2004, Porto, Portugal, September 29-October 1, 2004), Part I
    EditorsA.C. Campilho, M.S. Kamel
    Place of PublicationBerlin
    PublisherSpringer
    Pages1-8
    ISBN (Print)3-540-23223-0
    DOIs
    Publication statusPublished - 2004

    Publication series

    NameLecture Notes in Computer Science
    Volume3211
    ISSN (Print)0302-9743

    Fingerprint Dive into the research topics of 'Automatic image segmentation using a deformable model based on charged particles'. Together they form a unique fingerprint.

    Cite this