Abstract
Neural networks are widely used for solving pattern recognition problems [1–5]. Let us examine the following stages in the recognition of visual patterns: extraction of textural features; recognition of textures; extraction on the image of the regions with uniform texture; and the recognition of the shape of these regions. All these stages can be realized effectively on neurocomputers. Some statistical characteristics of the local sections of images usually are understood by textural features [6, 7]. We understand under the texture a property of the local section of the image, which is fixed in a certain extensive section of the image. The foliage of the trees, grass, asphalt coating, and so on can serve as examples of sections of images having identical texture.
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Kussul, E., Baidyk, T., Wunsch, D.C. (2010). Recognition of Textures, Object Shapes, and Handwritten Words. In: Neural Networks and Micromechanics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02535-8_6
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DOI: https://doi.org/10.1007/978-3-642-02535-8_6
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