Abstract
The recognition of textures involves multiple local filtering and subsequent averaging of the image to produce a feature space in which textures are represented as cluster centers. Results are presented for a two variate algorithm involving the features “brightness” and “roughness”. Both regular and random textures generated by program are used. The final result of classification is expressed in terms of the original textures: the computer “paints” what it has seen — and makes rather understandable errors at the borders between different textures.
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Triendl, E.E. Texturerkennung und Texturreproduktion. Kybernetik 13, 1–5 (1973). https://doi.org/10.1007/BF00289105
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DOI: https://doi.org/10.1007/BF00289105