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Image generation has been proposed for many different tasks in the literature, from physics events visualization to large databases creation, from creative design to the purpose of "art for art's sake". In this paper a new approach to computer image generation is presented: the method creates new images by randomizing the decompression process, starting from a compressed representation of an image by Iterate Function Systems. Petri Nets are employed both for modeling the decompression process and for inserting a randomization component in it. A second method proposed in this work directly translates the evolution of a Petri Net into a graphic output. Experimental results are given, showing different class of images generated by the two methods.
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3--11
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Bibliogr. 20 poz.,Rys., wykr.,
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bwmeta1.element.baztech-article-BAT2-0001-0637