In automated visual inspection, the evaluation of only one image is often not sufficient to obtain the desired information on a scene. Shortcomings originated from the image acquisition are caused by the projection of the world, the sampling and the quantization in spatial and temporal dimensions. In consequence, image acquisition is always a non-injective mapping. However, by acquiring image series where at least one acquisition parameter has been varied systematically, many relevant properties of the scene can be transferred into features that are in some way conserved in the image series. In this context, image fusion is the technique of gaining useful information about the scene by means of a sophisticated processing of an image series. That way, information can be gained that is not directly conceivable in a single image.


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    Title :

    Image fusion for automated visual inspection


    Contributors:

    Conference:

    2007


    Publication date :

    2007


    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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