This paper presents an effective use of local descriptors for object or scene recognition and indexing. This approach is in keeping with model-based recognition systems and consists of an extension of a standard point-to-point matching between two images. Aiming at this, we address the use of Full-Zernike moments as a reliable local characterization of the image signal. A fundamental characteristic of the used descriptors is then their ability to "absorb" a given set of potential image modifications. Their design calls principally for the theory of invariants. A built-in invariance to similarities allows one to manage narrow bounded perspective transformations. Moreover we provide a study of the substantial and costless contribution of the use of color information. In order to achieve photometric invariance, different types of normalization are evaluated through a model-based object recognition task.


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    Titel :

    A local color descriptor for efficient scene-object recognition


    Beteiligte:
    Bigorgne, E. (Autor:in) / Achard, C. (Autor:in) / Devars, J. (Autor:in)


    Erscheinungsdatum :

    01.01.2001


    Format / Umfang :

    592594 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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