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    Statistical Image Analysis for Image Evolution

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    Brock_Salimi_Elham_2016.pdf
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    Author
    Salimi, Elham
    Keyword
    Image analysis, Image evolution, Evolutionary arts, Statistical analysis, Lightweight image retrieval
    
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    URI
    http://hdl.handle.net/10464/10707
    Abstract
    This thesis is focused on using genetic programming to evolve images based on lightweight features extracted from a given target image. The main motivation of this thesis is research by Lombardi et al. in which an image retrieval system is developed based on lightweight statistical features of images for comparing and classifying them in painting style categories; primarily based on color matching. In this thesis, automatic fitness scoring of variations of up to 17 lightweight image features using many-objective fitness evaluation was used to evolve textures. Evolved results were shown to have similar color characteristics to target images. Although a human survey was conducted to confirm those results, it was inconclusive.
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    M.Sc. Computer Science

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