id: 05977932
dt: a
an: 05977932
au: Antúnez, Esther; Marfil, Rebeca; Bandera, Antonio
ti: A new perception-based segmentation approach using combinatorial pyramids.
so: Maino, Giuseppe (ed.) et al., Image analysis and processing ‒ ICIAP 2011.
    16th international conference, Ravenna, Italy, September 14‒16, 2011.
    Proceedings, Part I. Berlin: Springer (ISBN 978-3-642-24084-3/pbk).
    Lecture Notes in Computer Science 6978, 327-336 (2011).
py: 2011
pu: Berlin: Springer
la: EN
cc: 
ut: perceptual grouping; irregular pyramids; combinatorial pyramids
ci: 
li: doi:10.1007/978-3-642-24085-0_34
ab: Summary: This paper presents a bottom-up approach for perceptual
    segmentation of natural images. The segmentation algorithm consists of
    two consecutive stages: firstly, the input image is partitioned into a
    set of blobs of uniform colour (pre-segmentation stage) and then, using
    a more complex distance which integrates edge and region descriptors,
    these blobs are hierarchically merged (perceptual grouping). Both
    stages are addressed using the Combinatorial Pyramid, a hierarchical
    structure which can correctly encode relationships among image regions
    at upper levels. Thus, unlike other methods, the topology of the image
    is preserved. The performance of the proposed approach has been
    initially evaluated with respect to ground-truth segmentation data
    using the Berkeley Segmentation Dataset and Benchmark. Although
    additional descriptors must be added to deal with textured surfaces,
    experimental results reveal that the proposed perceptual grouping
    provides satisfactory scores.
rv: