id: 06107971
dt: a
an: 06107971
au: Herman, Gabor T.; Kong, T.Yung; Oliveira, Lucas M.
ti: Provably robust simplification of component trees of multidimensional
    images.
so: Brimkov, Valentin E. (ed.) et al., Digital geometry algorithms. Theoretical
    foundations and applications to computational imaging. New York, NY:
    Springer (ISBN 978-94-007-4173-7/hbk; 978-94-007-4174-4/ebook). Lecture
    Notes in Computational Vision and Biomechanics 2, 27-69 (2012).
py: 2012
pu: New York, NY: Springer
la: EN
cc: 
ut: multidimensional images; component trees; foreground component tree
    structure; macromolecular databases
ci: 
li: doi:10.1007/978-94-007-4174-4_2
ab: Summary: We are interested in translating $n$-dimensional arrays of real
    numbers (images) into simpler structures that nevertheless capture the
    topological/geometrical essence of the objects in the images. In the
    case $n=3$ these structures may be used as descriptors of images in
    macromolecular databases. A foreground component tree structure (FCTS)
    contains all the information on the relationships between connected
    components when the image is thresholded at various levels. But
    unsimplified FCTSs are too sensitive to errors in the image to be good
    descriptors. This chapter presents a method of simplifying FCTSs which
    can be proved to be robust in the sense of producing essentially the
    same simplifications in the presence of small perturbations. We
    demonstrate the potential applicability of our methodology to
    macromolecular databases by showing that the simplified FCTSs can be
    used to distinguish between two slightly different versions of an
    adenovirus.
rv: