In this paper, an unsupervised color vision system aimed at driving vehicles in real time on roads in a fast changing unknown real-world environment is described. The algorithms of the image processing unit enable us to deal with even low- saturated images and images with a poor contrast. They are not aimed merely at road finding, but at complete image classification and analysis and its qualitative and conceptual description as well. The algorithms exploit also a new concept of image texture and implement a new fast method for texture description to be used in real-time image segmentation. A subsystem of logical inference based on the proposed image description and applied in qualitative analysis of road scenes is also presented. This subsystem is able to seek in real time for objects with a qualitative description. Examples that illustrate the operation of the system are presented. The core part of the system, which does not take into account the particular properties of the object in the scene, can be used for a wide variety of problems (for instance, for traffic control, automated landing, and so on).


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    Titel :

    Unsupervised color vision system for driving unmanned vehicles


    Beteiligte:

    Kongress:

    Enhanced and Synthetic Vision 1998 ; 1998 ; Orlando,FL,USA


    Erschienen in:

    Erscheinungsdatum :

    30.07.1998





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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