We introduce a novel rich local descriptor of an image point, we call the (labeled) distance set, which is determined by the spatial arrangement of image features around that point. We describe a two-dimensional (2D) visual object by the set of (labeled) distance sets associated with the feature points of that object. Based on a dissimilarity measure between (labeled) distance sets and a dissimilarity measure between sets of (labeled) distance sets, we address two problems that are often encountered in object recognition: object segmentation, for which we formulate a distance sets shape filter, and shape matching. The use of the shape filter is illustrated on printed and handwritten character recognition and detection of traffic signs in complex scenes. The shape comparison procedure is illustrated on handwritten character classification, COIL-20 database object recognition and MPEG-7 silhouette database retrieval.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Distance sets for shape filters and shape recognition


    Contributors:
    Grigorescu, C. (author) / Petkov, N. (author)

    Published in:

    Publication date :

    2003


    Size :

    13 Seiten, 62 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Shape recognition based on Kernel-edit distance

    Daliri, M. R. / Torre, V. | British Library Online Contents | 2010


    Dynamic Distance-Based Shape Features for Gait Recognition

    Whytock, T. | British Library Online Contents | 2014


    ADR shape descriptor - Distance between shape centroids versus shape diameter

    Klette, R. / Zunic, J. | British Library Online Contents | 2012


    LANE SHAPE RECOGNITION SYSTEM AND LANE SHAPE RECOGNITION METHOD

    SATAKE TOSHIHIDE / TAKAGI FUMIAKI / SHIMIZU YUJI et al. | European Patent Office | 2022

    Free access

    LANE SHAPE RECOGNITION SYSTEM AND LANE SHAPE RECOGNITION METHOD

    SATAKE TOSHIHIDE / TAKAGI FUMIAKI / SHIMIZU YUJI et al. | European Patent Office | 2021

    Free access