We propose a segmentation method based on Polya's urn model for contagious phenomena. Initial labeling of the pixel is obtained using a Maximum Likelihood (ML) estimate or the Nearest Mean Classifier (NMC), which are used to determine the initial composition of an urn representing the pixel. The resulting urns are then subjected to a modified urn sampling scheme mimicking the development of an infection to yield a segmentation of the image into homogeneous regions. Examples of the application of this scheme to the segmentation of synthetic texture images, Ultra-Wideband Synthetic Aperture Radar (UWB SAR) images and Magnetic Resonance Images (MRI) are provided.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Contagion-driven image segmentation and labeling


    Contributors:
    Banerjee, A. (author) / Burlina, P. (author) / Alajaji, F. (author)


    Publication date :

    1998-01-01


    Size :

    967958 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Contagion-Driven Image Segmentation and Labeling

    Banerjee, A. / Burlina, P. / Alajaji, F. et al. | British Library Conference Proceedings | 1998


    Watershed-driven relaxation labeling for image segmentation

    Hansen, M.W. / Higgins, W.E. | IEEE | 1994


    Watershed-Driven Relaxation Labeling for Image Segmentation

    Hansen, M. W. / Higgins, W. E. / IEEE; Signal Processing Society | British Library Conference Proceedings | 1994


    A Multiphase Dynamic Labeling Model for Variational Recognition-driven Image Segmentation

    Cremers, D. / Sochen, N. / Schnörr, C. | British Library Online Contents | 2006


    Probabilistic Joint Image Segmentation and Labeling by Figure-Ground Composition

    Ion, A. / Carreira, J. o. / Sminchisescu, C. | British Library Online Contents | 2014