Solutions to real-world image-segmentation problems typically require many image-processing steps. Unfortunately, the user must decide how to construct this sequence of steps for a given problem. So far, no system has been proposed to make the construction of these processes "easy" for the user. As a result, segmentation processes are often laboriously developed by an image-processing expert. We describe a method for automatically generating image-segmentation processes for arbitrary images. Our method uses cue-based image analysis. The user provides problem-specific information via easily defined cues. Two types of cues can be defined: (1) iconic cues, which are image-based and constructed by drawing directly onto the image data; and (2) symbolic cues, which are verbally specified facts. The cues are interpreted to help select image-processing functions. The user need not be an image-processing expert-he must only understand the significance of the specified cues for a particular problem.<>


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automatic generation of image-segmentation processes


    Beteiligte:
    Reinhardt, J. (Autor:in) / Higgins, W.E. (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    610102 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Automatic Generation of Image-Segmentation Processes

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


    Techniques for Automatic Image Segmentation

    Kalivanov, A.Zh | Online Contents | 1999


    Techniques for Automatic Image Segmentation

    Kalivanov, A.Zh | Online Contents | 1999


    Automatic Image Segmentation by Tree Pruning

    Bergo, F. P. | British Library Online Contents | 2007


    Stochastic contour approach for automatic image segmentation

    Li, Z. / Fan, J. | British Library Online Contents | 2009